Aug 25, 2016 · This paper presents an interactive machine learning paradigm with experts in the loop for improving image grouping. We demonstrate that image ...
In our paradigm, dermatologists encode their domain knowledge about the medical images by grouping a small subset of images via a carefully designed interface.
Abstract: Image grouping in knowledge-rich domains is challenging, since domain knowledge and human expertise are key to transform image pixels into ...
In our paradigm, dermatologists encode their domain knowledge about the medical images by grouping a small subset of images via a carefully designed interface.
Jan 22, 2024 · Interactive medical image segmentation using deep learning with image-specific fine tuning. In IEEE Transactions on Medical Imaging 37, 1562 ...
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Aug 24, 2022 · We focused on introducing a modified medical image segmentation approach using CNN as a deep learning and three distinct proposed architectures, ...
This comprehensive review delivers an overview of recent advances in medical imaging using deep neural networks.
In this repo, we provide a paper list of active learning in the fields of medical image analysis and computer vision.
Missing: grouping | Show results with:grouping
The interac- tive learning process involves three stages: key- word prediction, caption generation, and model updates. First, the model predicts a list of key-.
Sep 28, 2020 · In this paper, we present a comprehensive thematic survey on medical image segmentation using deep learning techniques.