Skychain Prostate Cancer Solution: data preparation, framework and usage scenario

Data preparation

Histopathological slides for the training of the neural network were prepared and marked out by the specialists from Moscow Central Hospital. On each of the 560 histopathological slides, 8664 labels were marked out, where each belongs to 1 of 7 different classes. The distribution of labels by classes is given in the table below.

Classification of labels

Solution framework

To detect and confirm the pathologies present on the slide, it is necessary to make a full and comprehensive analysis of the slide. Some signs of cancer appear only at the highest magnification, that is, directly at the pixel level (nucleoli of the nuclei), while the rest are present only at the macro level (shape of glands, shape of groups of glands and others). Our solution is complex and consists of several neural networks, each of which contributes to the final solution. At the micro level, several networks with different architectures analyze the structures of gland cells and their nuclei.

Images with and without neural network labeling

Software for pathologists (usage scenario)

A medical institution connected to the system gets the opportunity to use technology that will help histologists to carry out faster and more accurate diagnostics for each patient. For each clinic, the necessary number of accounts will be provided for all doctors involved in decision-making in the diagnosis of histopathological slides.

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Blockchain infrastructure aimed to host, train and use artificial intelligence (AI) in healthcare. Our website: https://skychain.global/