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DICOM

通過 Java 對 DICOM 進行卡通化

使用服務器端 API 構建您自己的 Java 應用程序來卡通化 DICOM 文件。

如何使用 Java 將 DICOM 文件卡通化

卡通效果具有固有的吸引力，常常喚起懷舊的童年記憶。幾乎每一篇平面設計文章都將卡通圖像作為基本元素。卡通化肖像、微調燈光、轉換為黑白、嘗試顏色、混合各種編輯技術以及製作複雜的圖像效果都可以通過圖像濾鏡（例如AdjustBrightness、BinarizeFixed、Filter、ReplaceColor 和ApplyMask）來實現。這些濾鏡可以應用於原始加載的照片。無論您的網頁主題是什麼，卡通風格的圖像都適合用於插圖目的。科學文章變得充滿活力，而多樣化的內容對用戶更具吸引力，從而提高網站流量。為了卡通化 DICOM 文件，我們將使用 Aspose.Imaging for Java API 是一個功能豐富、功能強大易於使用的 Java 平台圖像處理和轉換 API。您可以直接從 Maven 並通過將以下配置添加到 pom.xml 將其安裝在基於 Maven 的項目中。

Repository<repository>
<id>AsposeJavaAPI</id>
<name>Aspose Java API</name>
<url>https://repository.aspose.com/repo/</url>
</repository>

Dependency<dependency>
<groupId>com.aspose</groupId>
<artifactId>aspose-imaging</artifactId>
<version>version of aspose-imaging API</version>
<classifier>jdk16</classifier>
</dependency>

通過 Java 對 DICOM 進行卡通化的步驟

你需要 aspose-imaging-version-jdk16.jar 在您自己的環境中嘗試以下工作流程。

使用 Image.Load 方法加載 DICOM 文件 +卡通化圖像；
以 Aspose.Imaging 支持的格式將壓縮圖像保存到光盤

系統要求

所有主要操作系統都支持 Java 的 Aspose.Imaging。只需確保您具有以下先決條件。

已安裝 JDK 1.6 或更高版本。

Cartoonify DICOM 圖像 - Java

	import com.aspose.imaging.*;
	import com.aspose.imaging.fileformats.png.PngImage;
	import com.aspose.imaging.imagefilters.filteroptions.FilterOptionsBase;
	import com.aspose.imaging.imagefilters.filteroptions.MedianFilterOptions;
	import com.aspose.imaging.imageoptions.PngOptions;
	import com.aspose.imaging.masking.ImageMasking;
	import com.aspose.imaging.masking.options.MaskingOptions;
	import java.io.File;
	import java.util.*;
	import java.util.function.Consumer;
	import java.util.function.Function;
	import java.util.stream.Collectors;



	cartoonify();

	public static void cartoonify()
	{
	filterImages(image ->
	{
	try (PngImage processedImage = new PngImage(image))
	{
	image.resize(image.getWidth() * 2, image.getHeight(), ResizeType.LeftTopToLeftTop);
	ImageFilterExtensions.cartoonify(processedImage);
	Graphics gr = new Graphics(image);
	gr.drawImage(processedImage, processedImage.getWidth(), 0);
	gr.drawLine(new Pen(Color.getDarkRed(), 3), processedImage.getWidth(), 0, processedImage.getWidth(), image.getHeight());
	}
	}, "cartoonify");
	}

	static String templatesFolder = "D:\\TestData\\";

	public static void filterImages(Consumer<RasterImage> doFilter, String filterName)
	{
	List<String> rasterFormats = Arrays.asList("jpg", "png", "bmp", "apng", "dicom",
	"jp2", "j2k", "tga", "webp", "tif", "gif", "ico");
	List<String> vectorFormats = Arrays.asList("svg", "otg", "odg", "eps", "wmf", "emf", "wmz", "emz", "cmx", "cdr");

	List<String> allFormats = new LinkedList<>(rasterFormats);
	allFormats.addAll(vectorFormats);

	allFormats.forEach(
	formatExt ->
	{
	String inputFile = templatesFolder + "template." + formatExt;
	boolean isVectorFormat = vectorFormats.contains(formatExt);

	//Need to rasterize vector formats before background remove
	if (isVectorFormat)
	{
	inputFile = rasterizeVectorImage(formatExt, inputFile);
	}

	String outputFile = templatesFolder + String.format("%s_%s.png", filterName, formatExt);

	System.out.println("Processing " + formatExt);

	try (RasterImage image = (RasterImage) Image.load(inputFile))
	{
	doFilter.accept(image);

	//If image is multipage save each page to png to demonstrate results
	if (image instanceof IMultipageImage && ((IMultipageImage) image).getPageCount() > 1)
	{
	IMultipageImage multiPage = (IMultipageImage) image;
	final int pageCount = multiPage.getPageCount();
	final Image[] pages = multiPage.getPages();
	for (int pageIndex = 0; pageIndex < pageCount; pageIndex++)
	{
	String fileName = String.format("%s_page%d_%s.png", filterName, pageIndex, formatExt);
	pages[pageIndex].save(fileName, new PngOptions());
	}
	}
	else
	{
	image.save(outputFile, new PngOptions());
	}
	}

	//Remove rasterized vector image
	if (isVectorFormat)
	{
	new File(inputFile).delete();
	}
	}
	);
	}

	private static String rasterizeVectorImage(String formatExt, String inputFile)
	{
	String outputFile = templatesFolder + "rasterized." + formatExt + ".png";
	try (Image image = Image.load(inputFile))
	{
	image.save(outputFile, new PngOptions());
	}

	return outputFile;
	}

	interface IImageDataContext
	{
	void applyData();
	}


	class ImageFilterExtensions
	{
	public static void cartoonify(RasterImage image)
	{
	try (RasterImage outlines = detectOutlines(image, Color.getBlack()))
	{
	image.adjustBrightness(30);
	image.filter(image.getBounds(), new MedianFilterOptions(7));

	Graphics gr = new Graphics(image);
	gr.drawImage(outlines, Point.getEmpty());
	}
	}

	public static RasterImage detectOutlines(RasterImage image, Color outlineColor)
	{
	PngImage outlines = new PngImage(image);

	IImageDataContext ctx = getDataContext(outlines);
	applyConvolutionFilter(ctx, ConvolutionFilterOptions.getBlur());
	applyConvolutionFilter(ctx, ConvolutionFilterOptions.getOutline());
	ctx.applyData();

	outlines.binarizeFixed((byte)30);
	ImageMasking.applyMask(outlines, outlines, new MaskingOptions()
	{{
	setBackgroundReplacementColor(Color.getTransparent());
	}});
	outlines.replaceColor(Color.fromArgb(255, 255, 255), (byte)0, outlineColor);
	applyConvolutionFilter(outlines, ConvolutionFilterOptions.getBlur());
	return outlines;
	}

	public static RasterImage applyOperationToRasterImage(RasterImage image, Consumer<RasterImage> operation)
	{
	if (image instanceof IMultipageImage)
	{
	IMultipageImage multipage = (IMultipageImage) image;
	for (Image page : multipage.getPages())
	{
	operation.accept((RasterImage) page);
	}
	}
	else
	{
	operation.accept(image);
	}

	return image;
	}

	public static RasterImage applyFilter(RasterImage image, FilterOptionsBase filterOptions)
	{
	return applyOperationToRasterImage(image, img ->
	img.filter(img.getBounds(), filterOptions));
	}

	public static RasterImage applyConvolutionFilter(RasterImage image, ConvolutionFilterOptions filterOptions)
	{
	return applyOperationToRasterImage(image, img ->
	{
	ImagePixelsLoader pixelsLoader = new ImagePixelsLoader(img.getBounds());
	img.loadPartialArgb32Pixels(img.getBounds(), pixelsLoader);
	PixelBuffer outBuffer = new PixelBuffer(img.getBounds(), new int[img.getWidth() * img.getHeight()]);
	ConvolutionFilter.doFiltering(pixelsLoader.getPixelsBuffer(), outBuffer, filterOptions);
	img.saveArgb32Pixels(outBuffer.getRectangle(), outBuffer.getPixels());
	});
	}

	public static IImageDataContext getDataContext(RasterImage image)
	{
	if (image instanceof IMultipageImage)
	{
	return new MultipageDataContext(
	Arrays.stream(((IMultipageImage)image).getPages()).map(page -> {
	ImageDataContext buf = new ImageDataContext((RasterImage) page);
	buf.setBuffer(getImageBuffer((RasterImage)page));
	return buf;
	}).collect(Collectors.toList()));
	}

	ImageDataContext buf = new ImageDataContext(image);
	buf.setBuffer(getImageBuffer(image));
	return buf;
	}

	static IPixelBuffer getImageBuffer(RasterImage img)
	{
	ImagePixelsLoader pixelsLoader = new ImagePixelsLoader(img.getBounds());
	img.loadPartialArgb32Pixels(img.getBounds(), pixelsLoader);
	return pixelsLoader.getPixelsBuffer();
	}

	public static IImageDataContext applyToDataContext(IImageDataContext dataContext,
	Function<IPixelBuffer, IPixelBuffer> processor)
	{
	if (dataContext instanceof MultipageDataContext)
	{
	for (ImageDataContext context : (MultipageDataContext) dataContext)
	{
	context.setBuffer(processor.apply(context.getBuffer()));
	}
	}

	if (dataContext instanceof ImageDataContext)
	{
	ImageDataContext ctx = (ImageDataContext)dataContext;
	ctx.setBuffer(processor.apply(ctx.getBuffer()));
	}

	return dataContext;
	}

	public static IImageDataContext applyConvolutionFilter(IImageDataContext dataContext,
	ConvolutionFilterOptions filterOptions)
	{
	return applyToDataContext(dataContext, buffer ->
	{
	PixelBuffer outBuffer = new PixelBuffer(buffer.getRectangle(), new int[buffer.getRectangle().getWidth() * buffer.getRectangle().getHeight()]);
	ConvolutionFilter.doFiltering(buffer, outBuffer, filterOptions);
	return outBuffer;
	});
	}
	}

	class ImageDataContext implements IImageDataContext
	{
	private final RasterImage image;
	private IPixelBuffer buffer;

	public ImageDataContext(RasterImage image)
	{
	this.image = image;
	}

	public RasterImage getImage()
	{
	return image;
	}

	public IPixelBuffer getBuffer()
	{
	return buffer;
	}

	public void setBuffer(IPixelBuffer buffer)
	{
	this.buffer = buffer;
	}

	public void applyData()
	{
	this.buffer.saveToImage(this.image);
	}
	}

	class MultipageDataContext extends LinkedList<ImageDataContext> implements IImageDataContext
	{
	public MultipageDataContext(Collection<ImageDataContext> enumerable)
	{
	addAll(enumerable);
	}

	public void applyData()
	{
	for (ImageDataContext context : this)
	{
	context.applyData();
	}
	}
	}

	class ImagePixelsLoader implements IPartialArgb32PixelLoader
	{
	private final CompositePixelBuffer pixelsBuffer;

	public ImagePixelsLoader(Rectangle rectangle)
	{
	this.pixelsBuffer = new CompositePixelBuffer(rectangle);
	}

	public CompositePixelBuffer getPixelsBuffer()
	{
	return pixelsBuffer;
	}

	@Override
	public void process(Rectangle pixelsRectangle, int[] pixels, Point start, Point end)
	{
	this.pixelsBuffer.addPixels(pixelsRectangle,pixels);
	}
	}

	interface IPixelBuffer
	{
	Rectangle getRectangle();
	int get(int x, int y);
	void set(int x, int y, int value);
	void saveToImage(RasterImage image);
	}

	class PixelBuffer implements IPixelBuffer
	{
	private final Rectangle rectangle;
	private final int[] pixels;
	public PixelBuffer(Rectangle rectangle,int[] pixels)
	{
	this.rectangle = rectangle;
	this.pixels = pixels;
	}

	@Override
	public com.aspose.imaging.Rectangle getRectangle()
	{
	return rectangle;
	}

	public int[] getPixels()
	{
	return pixels;
	}

	@Override
	public int get(int x, int y)
	{
	return pixels[getIndex(x,y)];
	}

	@Override
	public void set(int x, int y, int value)
	{
	pixels[getIndex(x,y)] = value;
	}

	public void saveToImage(RasterImage image)
	{
	image.saveArgb32Pixels(this.rectangle, this.pixels);
	}

	public boolean contains(int x,int y)
	{
	return this.rectangle.contains(x,y);
	}

	private int getIndex(int x,int y)
	{
	x -= this.rectangle.getLeft();
	y -= this.rectangle.getTop();
	return x + y * this.rectangle.getWidth();
	}
	}

	class CompositePixelBuffer implements IPixelBuffer
	{
	private final List<PixelBuffer> _buffers = new ArrayList<>();
	private final Rectangle rectangle;

	public CompositePixelBuffer(Rectangle rectangle)
	{
	this.rectangle = rectangle;
	}

	@Override
	public com.aspose.imaging.Rectangle getRectangle()
	{
	return rectangle;
	}

	@Override
	public int get(int x, int y)
	{
	return getBuffer(x,y).get(x, y);
	}

	@Override
	public void set(int x, int y, int value)
	{
	getBuffer(x, y).set(x, y, value);
	}

	@Override
	public void saveToImage(RasterImage image)
	{
	for (PixelBuffer buffer : this._buffers)
	{
	buffer.saveToImage(image);
	}
	}

	public void addPixels(Rectangle rectangle,int[] pixels)
	{
	if(rectangle.intersectsWith(rectangle))
	{
	this._buffers.add(new PixelBuffer(rectangle,pixels));
	}
	}

	private PixelBuffer getBuffer(int x,int y)
	{
	return this._buffers.stream().filter(b -> b.contains(x,y)).findFirst().get();
	}
	}

	class ConvolutionFilter
	{
	public static void doFiltering(
	IPixelBuffer inputBuffer,
	IPixelBuffer outputBuffer,
	ConvolutionFilterOptions options)
	{
	double factor = options.getFactor();
	int bias = options.getBias();
	double[][] kernel = options.getKernel();
	int filterWidth = kernel[0].length;
	int filterCenter = (filterWidth - 1) / 2;

	int x, y;
	int filterX, filterY, filterPx, filterPy, filterYPos, pixel;
	double r, g, b, kernelValue;

	int top = inputBuffer.getRectangle().getTop();
	int bottom = inputBuffer.getRectangle().getBottom();
	int left = inputBuffer.getRectangle().getLeft();
	int right = inputBuffer.getRectangle().getRight();

	for (y = top; y < bottom; y++)
	{
	for (x = left; x < right; x++)
	{
	r = 0;
	g = 0;
	b = 0;

	for (filterY = -filterCenter; filterY <= filterCenter; filterY++)
	{
	filterYPos = filterY + filterCenter;
	filterPy = filterY + y;

	if (filterPy >= top && filterPy < bottom)
	{
	for (filterX = -filterCenter; filterX <= filterCenter; filterX++)
	{
	filterPx = filterX + x;
	if (filterPx >= left && filterPx < right)
	{
	kernelValue = kernel[filterYPos][filterX + filterCenter];
	pixel = inputBuffer.get(filterPx, filterPy);
	r += ((pixel >> 16) & 0xFF) * kernelValue;
	g += ((pixel >> 8) & 0xFF) * kernelValue;
	b += (pixel & 0xFF) * kernelValue;
	}
	}
	}
	}

	r = (factor * r) + bias;
	g = (factor * g) + bias;
	b = (factor * b) + bias;
	r = r > 255 ? 255 : (r < 0 ? 0 : r);
	g = g > 255 ? 255 : (g < 0 ? 0 : g);
	b = b > 255 ? 255 : (b < 0 ? 0 : b);

	outputBuffer.set(x, y, (inputBuffer.get(x, y) & 0xFF000000) \| ((int)r << 16) \| ((int)g << 8) \| (int)b);
	}
	}
	}
	}

	class ConvolutionFilterOptions
	{
	private double factor = 1.0;

	public double getFactor()
	{
	return factor;
	}

	public void setFactor(double factor)
	{
	this.factor = factor;
	}

	private int bias = 0;

	public int getBias()
	{
	return bias;
	}

	public void setBias(int bias)
	{
	this.bias = bias;
	}

	private double[][] kernel;

	public double[][] getKernel()
	{
	return kernel;
	}

	public void setKernel(double[][] kernel)
	{
	this.kernel = kernel;
	}

	public ConvolutionFilterOptions()
	{

	}

	public ConvolutionFilterOptions(double[][] kernel)
	{
	this.kernel = kernel;
	}

	public static ConvolutionFilterOptions getBlur()
	{
	ConvolutionFilterOptions filterOptions = new ConvolutionFilterOptions();
	filterOptions.setKernel(new double[][] { { 1, 2, 1 }, { 2, 4, 2 }, { 1, 2, 1 } });
	filterOptions.setFactor(0.25 * 0.25);
	return filterOptions;
	}

	public static ConvolutionFilterOptions getSharpen()
	{
	return new ConvolutionFilterOptions(new double[][] { { 0, -1, 0 }, { -1, 5, -1 }, { 0, -1, 0 } });
	}

	public static ConvolutionFilterOptions getEmboss()
	{
	return new ConvolutionFilterOptions(new double[][] { { -2, -1, 0 }, { -1, 1, 1 }, { 0, 1, 2 } });
	}

	public static ConvolutionFilterOptions getOutline()
	{
	return new ConvolutionFilterOptions(new double[][] { { -1, -1, -1 }, { -1, 8, -1 }, { -1, -1, -1 } });
	}

	public static ConvolutionFilterOptions getBottomSobel()
	{
	return new ConvolutionFilterOptions(new double[][] { { -1, -2, -1 }, { 0, 0, 0 }, { 1, 2, 1 } });
	}

	public static ConvolutionFilterOptions getTopSobel()
	{
	return new ConvolutionFilterOptions(new double[][] { { 1, 2, 1 }, { 0, 0, 0 }, { -1, -2, -1 } });
	}

	public static ConvolutionFilterOptions getLeftSobel()
	{
	return new ConvolutionFilterOptions(new double[][] { { 1, 0, -1 }, { 2, 0, -2 }, { 1, 0, -1 } });
	}

	public static ConvolutionFilterOptions getRightSobel()
	{
	return new ConvolutionFilterOptions(new double[][] { { -1, 0, 1 }, { -2, 0, 2 }, { -1, 0, 1 } });
	}
	}

view raw cartoonify-images.java hosted with ❤ by GitHub

關於 Java API 的 Aspose.Imaging

Aspose.Imaging API 是一種圖像處理解決方案，用於在應用程序中創建、修改、繪製或轉換圖像（照片）。它提供：跨平台的圖像處理，包括但不限於各種圖像格式之間的轉換（包括統一的多頁或多幀圖像處理）、繪圖等修改、使用圖形基元、轉換（調整大小、裁剪、翻轉和旋轉）、二值化、灰度、調整）、高級圖像處理功能（過濾、抖動、遮罩、去偏斜）和內存優化策略。它是一個獨立的庫，不依賴任何軟件進行圖像操作。可以在項目中使用原生 API 輕鬆添加高性能圖像轉換功能。這些是 100% 私有的本地 API，圖像在您的服務器上處理。

通過在線應用程序卡通化 DICOM

通過訪問我們的 Live Demos 網站對 DICOM 文檔進行卡通化。現場演示有以下好處

無需下載或設置任何東西

無需編寫任何代碼

只需上傳您的 DICOM 文件並點擊 "Cartoonify now" 按鈕

立即獲取生成文件的下載鏈接

DICOM 什麼是 DICOM 文件格式

DICOM 是 Digital Imaging and Communications in Medicine 的首字母縮寫詞，屬於醫學信息學領域。 DICOM 是文件格式定義和網絡通信協議的結合。 DICOM 使用 .DCM 擴展名。 .DCM 以兩種不同的格式存在，即格式 1.x 和格式 2.x。 DCM Format 1.x 還提供兩個普通版本和擴展版本。 DICOM 用於集成來自不同供應商的打印機、服務器、掃描儀等醫療成像設備，還包含每個患者的唯一識別數據。如果 DICOM 文件能夠接收 DICOM 格式的圖像數據，則它們可以在兩方之間共享。 DICOM的通信部分是應用層協議，實體之間使用TCP/IP進行通信。 HTTP 和 HTTPS 協議用於 DICOM 的 Web 服務。 Web 服務支持的版本是 1.0、1.1、2 或更高版本。

其他支持的卡通化格式

使用 Java，可以輕鬆卡通化不同的格式，包括。

APNG (動畫便攜式網絡圖形)

BMP (位圖圖片)

ICO (窗口圖標)

JPG (聯合攝影專家組)

JPEG (聯合攝影專家組)

DIB (設備無關位圖)

DJVU (圖形格式)

DNG (數碼相機圖像)

EMF (增強的元文件格式)

EMZ (Windows 壓縮增強元文件)

GIF (圖形交換格式)

JP2 (JPEG 2000)

J2K (小波壓縮圖像)

PNG (便攜式網絡圖形)

TIFF (標記圖像格式)

TIF (標記圖像格式)

WEBP (光柵網絡圖像)

WMF (微軟視窗元文件)

WMZ (壓縮的 Windows Media Player 皮膚)

TGA (塔加圖形)

SVG (可縮放矢量圖形)

EPS (封裝的 PostScript 語言)

CDR (矢量繪圖圖像)

CMX (Corel 交換圖像)

OTG (開放文檔標準)

ODG (Apache OpenOffice 繪圖格式)

AVIF