Alexandr A. Kalinin

TL;DR: It is found that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art.

TL;DR: Albumentations as mentioned in this paper is a fast and flexible open source library for image augmentation with many various image transform operations available that is also an easy-to-use wrapper around other augmentation libraries.

TL;DR: Albumentations as mentioned in this paper is a fast and flexible library for image augmentation with many various image transform operations available, that is also an easy-to-use wrapper around other augmentation libraries.

TL;DR: This paper describes a deep learning-based approach for robotic instrument segmentation that addressed the binary segmentation problem, where every pixel in an image is labeled as an instrument or background from the surgery video feed.

TL;DR: Raghlin et al. as mentioned in this paper developed a computational approach based on deep convolution neural networks for breast cancer histology image classification, which utilizes several deep neural network architectures and gradient boosted trees classifier.