Histopathology Color Image Processing in Prostate Carcinoma

The interpretation of tissue images is the first step performed by the pathologist before render an accurate diagnosis. Digital Pathology is challenging to implement in developing countries since, due to the acquisition process, these images usually become low illuminated and contrasted, which significantly affects their analysis. Transformation of these low-quality images would be needed to improve the pathologist diagnosis process. This article aims to show the results obtained from a test carried out by three pathologists on a series of classic color manipulation algorithms that improve the information (i.e., nuclear shape, stroma, and gland formation) contained in prostate images. For this study, images from prostatic tissue supplied by the Instituto Caldense de Patologia (ICP) were used. Seven biopsy samples were used, each of them captured with 10x, 20x, and 40x magnifications, forming a total of 50 images. Then, a subjective quality test was performed by three pathologists. This test consisted of grading a series of 42 classical image processing algorithms on a scale of 0 to 4. The value 0 represents the worst rating (the new image did not provide any information), and 4 represents the best rating (the original image highlights exciting diagnosis features and offers essential information). 52.27% of the transformations were classified as useful (scores between 3-4) by the pathologists (23 of 44 in total). The color transformations succeeded in highlighting the different structures such as the cytoplasm, stroma, and nucleus, improving the perception of contours and shapes, which will help to render an accurate diagnosis.