Deep Learning in Medical Image Analysis

99 citations recorded by the source corpus.

Over recent years, deep learning (DL) has established itself as a powerful tool across a broad spectrum of domains in imaging-e [...].

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The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge (2019, methodology): “Throughout computer vision, methods based on Deep Learning (DL) now dominate (Litjens et al., 2017) and 3D segmentation is no exception (Shen et al., 2017).”
A Survey on Active Learning and Human-in-the-Loop Deep Learning for Medical Image Analysis (2019, methodology): “state-of-the-art technique for performing many medical image analysis tasks (Tizhoosh and Pantanowitz, 2018; Shen et al., 2017; Litjens et al., 2017; Suzuki, 2017).”
Medical image analysis using deep learning algorithms (2023, methodology): “The emergence of deep learning algorithms has prompted a notable transformation in the field of medical image analysis, as they have increasingly been employed to enhance the diagnosis, treatment, and monitoring of diverse medical conditions in recent years (9).”