Computerized spermatogenesis staging (CSS) of mouse testis sections via quantitative histomorphological analysis
We now have developed a Computerized Staging system of Spermatogenesis (CSS) for mouse testis sections through learning of an expert with decades of experience in mouse testis staging. The CSS system’s accuracy of mean and standard deviation (MSD) in identifying ES, MS, and LS were 0.93 ± 0.03, 0.94 ± 0.11, and 0.89 ± 0.05 and 0.85 ± 0.12, 0.88 ± 0.07, and 0.96 ± 0.04 for one with 5 years of experience, respectively. The CSS system’s accuracy of MSD in identifying stages VI, VII-mVIII, and late VIII are 0.74 ± 0.03, 0.85 ± 0.04, and 0.78 ± 0.06 and 0.34 ± 0.18, 0.78 ± 0.16, and 0.44 ± 0.25 for one with 5 years of experience, respectively. In terms of time it takes to collect these data, it takes on average 3 hours for a histologist and 1.87 hours for the CSS system to finish evaluating an entire testis section (computed with a PC (I7-6800k 4.0 GHzwith 32GB of RAM & 256G SSD) and a Titan 1080Ti GPU). Therefore, the CSS system is more accurate and faster compared to a human histologist in staging, and further optimization and development will not only lead to a complete staging of all 12 stages of mouse spermatogenesis but also could aid in the future diagnosis of human infertility. Moreover, the top-ranking histomorphological features identified by the CSS classifier are consistent with the primary features used by histologists in discriminating stages VI, VII-mVIII, and late VIII.
基于全景病理图像细胞密度和异型特征的胶质瘤自动分级
胶质瘤是最常见的恶性脑肿瘤，它的世界卫生组织（WHO）高低级别分类是制定治疗方案和预后的重要参考指标。临床中，脑胶质瘤的高低分级诊断通常由病理医生阅读全景病理图像（WSI）来完成，该任务繁琐且对医生经验要求高。根据2016年第4版《中枢神经系统肿瘤WHO分类》标准，细胞的富集程度、核异型、坏死等现象与胶质瘤分级密切相关，受该标准启发，本文定量分析脑全景病理图像中细胞密度和异型特征，对胶质瘤进行高低级别自动分级。首先分析全局细胞密度定位感兴趣区域（ROI），提取全扫描图像的全局密度特征，然后对感兴趣区域提取局部密度特征和异型特征，最后利用特征选择并构建平衡权重的支持向量机（SVM）分类器，5折交叉验证的受试者工作特性曲线下的面积（AUC）为0.92 ± 0.01，准确率（ACC）为0.82 ± 0.01。实验结果表明，本文提出的感兴趣区域定位方法可有效快速地定位，构建的细胞密度和异型特征能够实现胶质瘤的自动分级，为临床诊断提供可靠性依据。
