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⛄ 内容介绍
疟疾是全球主要的健康威胁之一，根据世界卫生组织最新报告，每年全世界因疟疾致死人数达四十万。及时准确的疟疾诊断是疟疾后续治疗和防控的关键，然而当前疟疾诊断主要依赖于有经验的专业技师，且每位病人诊断约需30分钟，因此使用人工智能技术对疟疾显微镜图像上的各类细胞进行快速准确的自动分割与分类具有重要的临床意义和应用价值。 本文提出了基于深度学习的疟疾显微镜图像细胞分割与分类算法，实现高精度的细胞自动分割与分类，同时实现分割与分类的一体化，以协助疟疾的临床诊断。
⛄ 部分代码
%createMask Threshold RGB image using auto-generated code from colorThresholder app.
% [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
% auto-generated code from the colorThresholder app. The colorspace and
% range for each channel of the colorspace were set within the app. The
% segmentation mask is returned in BW, and a composite of the mask and
% original RGB images is returned in maskedRGBImage.
%------------------------------------------------------
% Convert RGB image to chosen color space
I = RGB;
% Define thresholds for channel 1 based on histogram settings
channel1Min = 100.000;
channel1Max = 192.000;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.000;
channel2Max = 80.000;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 25.000;
channel3Max = 168.000;
% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end
⛄ 运行结果
⛄ 参考文献
[1]于旭燕刘建霞薛文渲袁晓辉段淑斐程永强. 基于改进CNN的糖尿病视网膜病变图像分类模型研究[J]. 现代电子技术, 2021, 044(020):168-172.
[2]沈玉红. 基于深度学习的疟疾显微镜图像细胞分割及分类算法研究[D]. 北京交通大学.
