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首页> 外文期刊>Biomedical signal processing and control >GPU accelerated stratified squamous epithelium biopsy image segmentation for OSCC detector and classifier
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GPU accelerated stratified squamous epithelium biopsy image segmentation for OSCC detector and classifier

机译：用于OSCC检测器和分类器的GPU加速分层鳞状上皮活检图像分割

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摘要

Automatic cancer detection and classification is one of the open research problems. Oral squamous cell carcinoma (OSCC) is prevalent among oral cancer patients. Traditional procedures of detection and classification of biopsy specimen are tedious and clinico pathological acumen. Most of the computer aided biomedical image analysis algorithms suffer from slow speed due to central processing unit (CPU) based sequential implementation. Adapting parallel processing for such algorithms can improve operational speed of such algorithms. In this work, NVIDIA graphical processing unit (GPU) GeForce GTX 1050Ti is used to offload segmentation process and part of Laws texture feature calculations in stratified squamous epithelium biopsy image classifier (SSE-BIC) from CPU. SSE-BIC detects and classifies oral SSE images either normal or one of the three grades of malignancy. Image segmentation of SSE-BIC is implemented using GPU which includes 2-D convolution, principal component analysis (PCA) and k-means clustering. 2-D convolution employed for Laws texture features also implemented using GPU. In this way, CPU based serial executable classifier SSE-BIC is altered to accommodate parallel processing and compared with the CPU implementation. Results showed that parallel implementation is about 13.04X times faster than the serial CPU implementation of SSE-BIC.
机译：自动癌症检测和分类是开放的研究问题之一。口腔鳞状细胞癌（OSCC）在口腔癌患者中普遍存在。活检标本的传统检测程序和分类是乏味和临床病理癌症。大多数计算机辅助生物医学图像分析算法由于基于中央处理单元（CPU）的顺序实现而遭受慢速速度。对这种算​​法的并行处理可以提高这种算法的操作速度。在这项工作中，NVIDIA图形处理单元（GPU）GeForce GTX 1050Ti用于卸载分层鳞状上皮活检图像分类器（SSE-BIC）的分层纹理特征计算。 SSE-BIC检测和分类口头上的图像，无论是正常的还是三个阶段的恶性肿瘤。使用GPU实现SSE-BIC的图像分割，该GPU包括2-D卷积，主成分分析（PCA）和K-Means集群。用于法律纹理特征的2-D卷积也使用GPU实现。以这种方式，基于CPU的串行可执行分类器SSE-BIC被改变以适应并行处理并与CPU实现进行比较。结果表明，平行实施比SSE-BIC的串行CPU实现速度快约13.04倍。

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