Medical image segmentation plays a critical role in healthcare, aiding in early disease detection and treatment planning. However, challenges such as variability in object appearances, indistinct ...

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Scikit-image offers a wide range of functions for image processing, such as image filtering, segmentation, feature detection, and more. It is widely used in various applications like biomedical ...

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“Here they tend to be used in parallel with existing clinical management policies and often either for assisting diagnostics and/or speeding up processes like image segmentation,” he said. Ewen ...

An architecture that can bridge the instrument gap and provide unified training for different modalities images is the development direction of medical image segmentation. However, existing methods ...

IEEE Transactions on Pattern Analysis and Machine Intelligence., 8: 679-698. [2] Meribout M. and al., 1999. Real-Time Image Segmentation on a Massively Parallel Architecture. Journal of Real-Time ...

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To address these issues, we propose a new co-training framework for segmentation modeling with automatic filtering to reduce the negative effects caused by noisy labels in the training dataset. Our ...