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Medical-Image-Processing-with-Java

What is Image Processing? Image processing is the field of computer science that deals with the manipulation and analysis of digital images. It is used in a variety of applications, including medical imaging, machine vision, and computer graphics.

In medical imaging, image processing techniques are used to improve the quality and clarity of medical images, extract information from the images, and assist in the diagnosis and treatment of medical conditions. These techniques can include image filtering, which removes noise and enhances image features; feature extraction, which extracts information about the shape, size, and texture of structures in the image; and image segmentation, which divides the image into regions of interest.

Programs

The following programs are included in this repository:

Invert Colors

The Invert Colors program demonstrates how to invert the colors of an image. It loads an image file, loops through all the pixels, extracts the red, green, and blue components, and inverts their values. It then saves the modified image.

Median Filter

The Median Filter program demonstrates how to apply a median filter to an image. A median filter is a type of image filter that replaces each pixel with the median value of its neighbors. This can be used to smooth out noise and improve the overall appearance of the image.

Edge Detection

The Edge Detection program demonstrates how to detect edges in an image using the Sobel operator. The Sobel operator is a popular edge detection technique that calculates the gradient of the image in the x and y directions. It then combines these gradients to identify strong edges in the image.

Image Segmentation

The Image Segmentation program demonstrates how to segment an image into regions of interest using the k-means clustering algorithm. K-means clustering is a machine learning technique that divides a set of data points into clusters based on their similarity. In this program, the k-means algorithm is used to divide the pixels in the image into clusters based on their color values.

Requirements

To run these programs, you will need the following:

Java 8 or higher Apache Maven (optional, for building the programs) Usage To run one of the programs, first clone this repository and navigate to the directory of the program you want to run. For example, to run the Invert Colors program:

To use these programs, you will need to have the following software installed on your computer:

Java Development Kit (JDK) An integrated development environment (IDE) such as Eclipse or IntelliJ IDEA Once you have these tools installed, you can clone or download this repository and open the programs in your IDE. You will need to provide your own input images, which can be in any format supported by the Java ImageIO class (such as JPEG, PNG, or BMP).

Additional Resources

For more information on medical image processing and Java, check out the following resources:

Java Image Processing Recipes by H. M. Deitel and P. J. Deitel [Java for Bio-Medical Engineers and Scientists](https://www.wiley.com/en-us/Java+for+Bio Medical+Engineers+and+Scientists-p-9781118892391) by Lou C. Alexander Java Image Processing Cookbook by Nick Whitelegg

About

A collection of Java programs for processing and analyzing medical images, including CT scans, MRIs, and X-rays

Resources

Readme
MIT license
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Stars

1 star

Watchers

1 watching

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Medical-Image-Processing-with-Java
What is Image Processing?
Image processing is the field of computer science that deals with the manipulation and analysis of digital images. It is used in a variety of applications, including medical imaging, machine vision, and computer graphics.
In medical imaging, image processing techniques are used to improve the quality and clarity of medical images, extract information from the images, and assist in the diagnosis and treatment of medical conditions. These techniques can include image filtering, which removes noise and enhances image features; feature extraction, which extracts information about the shape, size, and texture of structures in the image; and image segmentation, which divides the image into regions of interest.
Programs
The following programs are included in this repository:
Invert Colors
The Invert Colors program demonstrates how to invert the colors of an image. It loads an image file, loops through all the pixels, extracts the red, green, and blue components, and inverts their values. It then saves the modified image.
Median Filter
The Median Filter program demonstrates how to apply a median filter to an image. A median filter is a type of image filter that replaces each pixel with the median value of its neighbors. This can be used to smooth out noise and improve the overall appearance of the image.
Edge Detection
The Edge Detection program demonstrates how to detect edges in an image using the Sobel operator. The Sobel operator is a popular edge detection technique that calculates the gradient of the image in the x and y directions. It then combines these gradients to identify strong edges in the image.
Image Segmentation
The Image Segmentation program demonstrates how to segment an image into regions of interest using the k-means clustering algorithm. K-means clustering is a machine learning technique that divides a set of data points into clusters based on their similarity. In this program, the k-means algorithm is used to divide the pixels in the image into clusters based on their color values.
Requirements
To run these programs, you will need the following:
Java 8 or higher
Apache Maven (optional, for building the programs)
Usage
To run one of the programs, first clone this repository and navigate to the directory of the program you want to run. For example, to run the Invert Colors program:
To use these programs, you will need to have the following software installed on your computer:
Java Development Kit (JDK)
An integrated development environment (IDE) such as Eclipse or IntelliJ IDEA
Once you have these tools installed, you can clone or download this repository and open the programs in your IDE. You will need to provide your own input images, which can be in any format supported by the Java ImageIO class (such as JPEG, PNG, or BMP).
Additional Resources
For more information on medical image processing and Java, check out the following resources:
Java Image Processing Recipes by H. M. Deitel and P. J. Deitel
[Java for Bio-Medical Engineers and Scientists](https://www.wiley.com/en-us/Java+for+Bio Medical+Engineers+and+Scientists-p-9781118892391) by Lou C. Alexander
Java Image Processing Cookbook by Nick Whitelegg
About
A collection of Java programs for processing and analyzing medical images, including CT scans, MRIs, and X-rays
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Medical-Image-Processing-with-Java
What is Image Processing?
Image processing is the field of computer science that deals with the manipulation and analysis of digital images. It is used in a variety of applications, including medical imaging, machine vision, and computer graphics.
In medical imaging, image processing techniques are used to improve the quality and clarity of medical images, extract information from the images, and assist in the diagnosis and treatment of medical conditions. These techniques can include image filtering, which removes noise and enhances image features; feature extraction, which extracts information about the shape, size, and texture of structures in the image; and image segmentation, which divides the image into regions of interest.
Programs
The following programs are included in this repository:
Invert Colors
The Invert Colors program demonstrates how to invert the colors of an image. It loads an image file, loops through all the pixels, extracts the red, green, and blue components, and inverts their values. It then saves the modified image.
Median Filter
The Median Filter program demonstrates how to apply a median filter to an image. A median filter is a type of image filter that replaces each pixel with the median value of its neighbors. This can be used to smooth out noise and improve the overall appearance of the image.
Edge Detection
The Edge Detection program demonstrates how to detect edges in an image using the Sobel operator. The Sobel operator is a popular edge detection technique that calculates the gradient of the image in the x and y directions. It then combines these gradients to identify strong edges in the image.
Image Segmentation
The Image Segmentation program demonstrates how to segment an image into regions of interest using the k-means clustering algorithm. K-means clustering is a machine learning technique that divides a set of data points into clusters based on their similarity. In this program, the k-means algorithm is used to divide the pixels in the image into clusters based on their color values.
Requirements
To run these programs, you will need the following:
Java 8 or higher
Apache Maven (optional, for building the programs)
Usage
To run one of the programs, first clone this repository and navigate to the directory of the program you want to run. For example, to run the Invert Colors program:
To use these programs, you will need to have the following software installed on your computer:
Java Development Kit (JDK)
An integrated development environment (IDE) such as Eclipse or IntelliJ IDEA
Once you have these tools installed, you can clone or download this repository and open the programs in your IDE. You will need to provide your own input images, which can be in any format supported by the Java ImageIO class (such as JPEG, PNG, or BMP).
Additional Resources
For more information on medical image processing and Java, check out the following resources:
Java Image Processing Recipes by H. M. Deitel and P. J. Deitel
[Java for Bio-Medical Engineers and Scientists](https://www.wiley.com/en-us/Java+for+Bio Medical+Engineers+and+Scientists-p-9781118892391) by Lou C. Alexander
Java Image Processing Cookbook by Nick Whitelegg
About
A collection of Java programs for processing and analyzing medical images, including CT scans, MRIs, and X-rays
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Medical-Image-Processing-with-Java
What is Image Processing?
Image processing is the field of computer science that deals with the manipulation and analysis of digital images. It is used in a variety of applications, including medical imaging, machine vision, and computer graphics.
In medical imaging, image processing techniques are used to improve the quality and clarity of medical images, extract information from the images, and assist in the diagnosis and treatment of medical conditions. These techniques can include image filtering, which removes noise and enhances image features; feature extraction, which extracts information about the shape, size, and texture of structures in the image; and image segmentation, which divides the image into regions of interest.
Programs
The following programs are included in this repository:
Invert Colors
The Invert Colors program demonstrates how to invert the colors of an image. It loads an image file, loops through all the pixels, extracts the red, green, and blue components, and inverts their values. It then saves the modified image.
Median Filter
The Median Filter program demonstrates how to apply a median filter to an image. A median filter is a type of image filter that replaces each pixel with the median value of its neighbors. This can be used to smooth out noise and improve the overall appearance of the image.
Edge Detection
The Edge Detection program demonstrates how to detect edges in an image using the Sobel operator. The Sobel operator is a popular edge detection technique that calculates the gradient of the image in the x and y directions. It then combines these gradients to identify strong edges in the image.
Image Segmentation
The Image Segmentation program demonstrates how to segment an image into regions of interest using the k-means clustering algorithm. K-means clustering is a machine learning technique that divides a set of data points into clusters based on their similarity. In this program, the k-means algorithm is used to divide the pixels in the image into clusters based on their color values.
Requirements
To run these programs, you will need the following:
Java 8 or higher
Apache Maven (optional, for building the programs)
Usage
To run one of the programs, first clone this repository and navigate to the directory of the program you want to run. For example, to run the Invert Colors program:
To use these programs, you will need to have the following software installed on your computer:
Java Development Kit (JDK)
An integrated development environment (IDE) such as Eclipse or IntelliJ IDEA
Once you have these tools installed, you can clone or download this repository and open the programs in your IDE. You will need to provide your own input images, which can be in any format supported by the Java ImageIO class (such as JPEG, PNG, or BMP).
Additional Resources
For more information on medical image processing and Java, check out the following resources:
Java Image Processing Recipes by H. M. Deitel and P. J. Deitel
[Java for Bio-Medical Engineers and Scientists](https://www.wiley.com/en-us/Java+for+Bio Medical+Engineers+and+Scientists-p-9781118892391) by Lou C. Alexander
Java Image Processing Cookbook by Nick Whitelegg
About
A collection of Java programs for processing and analyzing medical images, including CT scans, MRIs, and X-rays
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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Medical-Image-Processing-with-Java
What is Image Processing?
Image processing is the field of computer science that deals with the manipulation and analysis of digital images. It is used in a variety of applications, including medical imaging, machine vision, and computer graphics.
In medical imaging, image processing techniques are used to improve the quality and clarity of medical images, extract information from the images, and assist in the diagnosis and treatment of medical conditions. These techniques can include image filtering, which removes noise and enhances image features; feature extraction, which extracts information about the shape, size, and texture of structures in the image; and image segmentation, which divides the image into regions of interest.
Programs
The following programs are included in this repository:
Invert Colors
The Invert Colors program demonstrates how to invert the colors of an image. It loads an image file, loops through all the pixels, extracts the red, green, and blue components, and inverts their values. It then saves the modified image.
Median Filter
The Median Filter program demonstrates how to apply a median filter to an image. A median filter is a type of image filter that replaces each pixel with the median value of its neighbors. This can be used to smooth out noise and improve the overall appearance of the image.
Edge Detection
The Edge Detection program demonstrates how to detect edges in an image using the Sobel operator. The Sobel operator is a popular edge detection technique that calculates the gradient of the image in the x and y directions. It then combines these gradients to identify strong edges in the image.
Image Segmentation
The Image Segmentation program demonstrates how to segment an image into regions of interest using the k-means clustering algorithm. K-means clustering is a machine learning technique that divides a set of data points into clusters based on their similarity. In this program, the k-means algorithm is used to divide the pixels in the image into clusters based on their color values.
Requirements
To run these programs, you will need the following:
Java 8 or higher
Apache Maven (optional, for building the programs)
Usage
To run one of the programs, first clone this repository and navigate to the directory of the program you want to run. For example, to run the Invert Colors program:
To use these programs, you will need to have the following software installed on your computer:
Java Development Kit (JDK)
An integrated development environment (IDE) such as Eclipse or IntelliJ IDEA
Once you have these tools installed, you can clone or download this repository and open the programs in your IDE. You will need to provide your own input images, which can be in any format supported by the Java ImageIO class (such as JPEG, PNG, or BMP).
Additional Resources
For more information on medical image processing and Java, check out the following resources:
Java Image Processing Recipes by H. M. Deitel and P. J. Deitel
[Java for Bio-Medical Engineers and Scientists](https://www.wiley.com/en-us/Java+for+Bio Medical+Engineers+and+Scientists-p-9781118892391) by Lou C. Alexander
Java Image Processing Cookbook by Nick Whitelegg
About
A collection of Java programs for processing and analyzing medical images, including CT scans, MRIs, and X-rays
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Medical-Image-Processing-with-Java
What is Image Processing?
Image processing is the field of computer science that deals with the manipulation and analysis of digital images. It is used in a variety of applications, including medical imaging, machine vision, and computer graphics.
In medical imaging, image processing techniques are used to improve the quality and clarity of medical images, extract information from the images, and assist in the diagnosis and treatment of medical conditions. These techniques can include image filtering, which removes noise and enhances image features; feature extraction, which extracts information about the shape, size, and texture of structures in the image; and image segmentation, which divides the image into regions of interest.
Programs
The following programs are included in this repository:
Invert Colors
The Invert Colors program demonstrates how to invert the colors of an image. It loads an image file, loops through all the pixels, extracts the red, green, and blue components, and inverts their values. It then saves the modified image.
Median Filter
The Median Filter program demonstrates how to apply a median filter to an image. A median filter is a type of image filter that replaces each pixel with the median value of its neighbors. This can be used to smooth out noise and improve the overall appearance of the image.
Edge Detection
The Edge Detection program demonstrates how to detect edges in an image using the Sobel operator. The Sobel operator is a popular edge detection technique that calculates the gradient of the image in the x and y directions. It then combines these gradients to identify strong edges in the image.
Image Segmentation
The Image Segmentation program demonstrates how to segment an image into regions of interest using the k-means clustering algorithm. K-means clustering is a machine learning technique that divides a set of data points into clusters based on their similarity. In this program, the k-means algorithm is used to divide the pixels in the image into clusters based on their color values.
Requirements
To run these programs, you will need the following:
Java 8 or higher
Apache Maven (optional, for building the programs)
Usage
To run one of the programs, first clone this repository and navigate to the directory of the program you want to run. For example, to run the Invert Colors program:
To use these programs, you will need to have the following software installed on your computer:
Java Development Kit (JDK)
An integrated development environment (IDE) such as Eclipse or IntelliJ IDEA
Once you have these tools installed, you can clone or download this repository and open the programs in your IDE. You will need to provide your own input images, which can be in any format supported by the Java ImageIO class (such as JPEG, PNG, or BMP).
Additional Resources
For more information on medical image processing and Java, check out the following resources:
Java Image Processing Recipes by H. M. Deitel and P. J. Deitel
[Java for Bio-Medical Engineers and Scientists](https://www.wiley.com/en-us/Java+for+Bio Medical+Engineers+and+Scientists-p-9781118892391) by Lou C. Alexander
Java Image Processing Cookbook by Nick Whitelegg
About
A collection of Java programs for processing and analyzing medical images, including CT scans, MRIs, and X-rays
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Medical-Image-Processing-with-Java
What is Image Processing?
Image processing is the field of computer science that deals with the manipulation and analysis of digital images. It is used in a variety of applications, including medical imaging, machine vision, and computer graphics.
In medical imaging, image processing techniques are used to improve the quality and clarity of medical images, extract information from the images, and assist in the diagnosis and treatment of medical conditions. These techniques can include image filtering, which removes noise and enhances image features; feature extraction, which extracts information about the shape, size, and texture of structures in the image; and image segmentation, which divides the image into regions of interest.
Programs
The following programs are included in this repository:
Invert Colors
The Invert Colors program demonstrates how to invert the colors of an image. It loads an image file, loops through all the pixels, extracts the red, green, and blue components, and inverts their values. It then saves the modified image.
Median Filter
The Median Filter program demonstrates how to apply a median filter to an image. A median filter is a type of image filter that replaces each pixel with the median value of its neighbors. This can be used to smooth out noise and improve the overall appearance of the image.
Edge Detection
The Edge Detection program demonstrates how to detect edges in an image using the Sobel operator. The Sobel operator is a popular edge detection technique that calculates the gradient of the image in the x and y directions. It then combines these gradients to identify strong edges in the image.
Image Segmentation
The Image Segmentation program demonstrates how to segment an image into regions of interest using the k-means clustering algorithm. K-means clustering is a machine learning technique that divides a set of data points into clusters based on their similarity. In this program, the k-means algorithm is used to divide the pixels in the image into clusters based on their color values.
Requirements
To run these programs, you will need the following:
Java 8 or higher
Apache Maven (optional, for building the programs)
Usage
To run one of the programs, first clone this repository and navigate to the directory of the program you want to run. For example, to run the Invert Colors program:
To use these programs, you will need to have the following software installed on your computer:
Java Development Kit (JDK)
An integrated development environment (IDE) such as Eclipse or IntelliJ IDEA
Once you have these tools installed, you can clone or download this repository and open the programs in your IDE. You will need to provide your own input images, which can be in any format supported by the Java ImageIO class (such as JPEG, PNG, or BMP).
Additional Resources
For more information on medical image processing and Java, check out the following resources:
Java Image Processing Recipes by H. M. Deitel and P. J. Deitel
[Java for Bio-Medical Engineers and Scientists](https://www.wiley.com/en-us/Java+for+Bio Medical+Engineers+and+Scientists-p-9781118892391) by Lou C. Alexander
Java Image Processing Cookbook by Nick Whitelegg
About
A collection of Java programs for processing and analyzing medical images, including CT scans, MRIs, and X-rays
Resources
Readme
MIT license
Activity
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1 star
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1 watching
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0 forks
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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Medical-Image-Processing-with-Java
What is Image Processing?
Image processing is the field of computer science that deals with the manipulation and analysis of digital images. It is used in a variety of applications, including medical imaging, machine vision, and computer graphics.
In medical imaging, image processing techniques are used to improve the quality and clarity of medical images, extract information from the images, and assist in the diagnosis and treatment of medical conditions. These techniques can include image filtering, which removes noise and enhances image features; feature extraction, which extracts information about the shape, size, and texture of structures in the image; and image segmentation, which divides the image into regions of interest.
Programs
The following programs are included in this repository:
Invert Colors
The Invert Colors program demonstrates how to invert the colors of an image. It loads an image file, loops through all the pixels, extracts the red, green, and blue components, and inverts their values. It then saves the modified image.
Median Filter
The Median Filter program demonstrates how to apply a median filter to an image. A median filter is a type of image filter that replaces each pixel with the median value of its neighbors. This can be used to smooth out noise and improve the overall appearance of the image.
Edge Detection
The Edge Detection program demonstrates how to detect edges in an image using the Sobel operator. The Sobel operator is a popular edge detection technique that calculates the gradient of the image in the x and y directions. It then combines these gradients to identify strong edges in the image.
Image Segmentation
The Image Segmentation program demonstrates how to segment an image into regions of interest using the k-means clustering algorithm. K-means clustering is a machine learning technique that divides a set of data points into clusters based on their similarity. In this program, the k-means algorithm is used to divide the pixels in the image into clusters based on their color values.
Requirements
To run these programs, you will need the following:
Java 8 or higher
Apache Maven (optional, for building the programs)
Usage
To run one of the programs, first clone this repository and navigate to the directory of the program you want to run. For example, to run the Invert Colors program:
To use these programs, you will need to have the following software installed on your computer:
Java Development Kit (JDK)
An integrated development environment (IDE) such as Eclipse or IntelliJ IDEA
Once you have these tools installed, you can clone or download this repository and open the programs in your IDE. You will need to provide your own input images, which can be in any format supported by the Java ImageIO class (such as JPEG, PNG, or BMP).
Additional Resources
For more information on medical image processing and Java, check out the following resources:
Java Image Processing Recipes by H. M. Deitel and P. J. Deitel
[Java for Bio-Medical Engineers and Scientists](https://www.wiley.com/en-us/Java+for+Bio Medical+Engineers+and+Scientists-p-9781118892391) by Lou C. Alexander
Java Image Processing Cookbook by Nick Whitelegg
About
A collection of Java programs for processing and analyzing medical images, including CT scans, MRIs, and X-rays
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors