Data-Driven Deep Supervision for Medical Image Segmentation

Medical image segmentation plays a vital role in disease diagnosis and analysis. However, data-dependent difficulties such as low image contrast, noisy background, and complicated objects of interest render the segmentation problem challenging. These difficulties diminish dense prediction and make i...

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Veröffentlicht in:	IEEE transactions on medical imaging 2022-06, Vol.41 (6), p.1560-1574
Hauptverfasser:	Mishra, Suraj, Zhang, Yizhe, Chen, Danny Z., Hu, X. Sharon
Format:	Artikel
Sprache:	eng
Schlagworte:	2D and 3D images Artificial neural networks Background noise Blood vessels Convolutional neural network Convolutional neural networks Datasets deep supervision Feature extraction Image contrast Image processing Image Processing, Computer-Assisted - methods Image segmentation Localization Lymph nodes Medical imaging Melanoma Neural networks Neural Networks, Computer Optical imaging Optical sensors Predictions receptive field Retinal Vessels Robustness segmentation Spleen Supervision Three-dimensional displays
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