The increase histopathological evaluation of prostatectomy specimens rises the workload on pathologists. Automated histopathology systems, preferably directly on unstained specimens, would accelerate the pathology workflow. In this study, we investigate the potential of quantitative analysis of optical coherence tomography (OCT) to separate benign from malignant prostate tissue automatically.
View Article and Find Full Text PDFPurpose: Histological grade is an important prognostic factor in patients with non-muscle-invasive bladder cancer (NMIBC). However, interobserver variability is high. Previous studies have suggested that quantification of histological features is useful to objectify grading.
View Article and Find Full Text PDFDiagnostic accuracy of needle-based optical coherence tomography (OCT) for prostate cancer detection by visual and quantitative analysis is defined. 106 three-dimensional (3-D)-OCT data sets were acquired in 20 prostates after radical prostatectomy and precisely matched with pathology. OCT images were grouped per histological category.
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