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Интеллектуальная Система Тематического Исследования НАукометрических данных |
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How to predict the ISUP grade of prostate biopsies scans with a combination of CNN and RNN.доклад на конференции
- Автор: Гречка Д.А.
- Международная Конференция (Семинар (workshop)) : PANDA workshop, a satellite event of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2020
- Даты проведения конференции: 8 октября 2020
- Дата доклада: 8 октября 2020
- Тип доклада: Устный
- Докладчик: Гречка Д.А.
- Место проведения: Лима, Peru
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Аннотация доклада:
Presenting the approach to building an automated system for grading the microscopy scans of biopsied tissue. The system consists of convolutional neural network (CNN) and a recurrent neural network (RNN) chained together to predict the ISUP grade group of a tissue sample. High resolution microscopy scan is split into a grid of smaller square tiles. Each tile containing the tissue is mapped into a feature vector by applying the CNN (DenseNet121). Then feature vectors (presented as a sequence) are passed to RNN (GRU units) to evaluate the presence of cancerous tissue and to assign a corresponding grade group.
- Добавил в систему: Гречка Дмитрий Андреевич