Pathological image classification
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The development of digital imaging technology is creating extraordinary levels of accuracy that provide support for improved reliability in different aspects of the image analysis, such as content-based image retrieval, image segmentation, and classification.
17p vikentucky2711 26-11-2020 9 0 Download
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Due to the recent advances in deep learning, this model attracted researchers who have applied it to medical image analysis. However, pathological image analysis based on deep learning networks faces a number of challenges, such as the high resolution (gigapixel) of pathological images and the lack of annotation capabilities.
15p vijisoo2711 27-10-2020 12 1 Download
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The value of the CT features and quantitative analysis of lung subsolid nodules (SSNs) in the prediction of the pathological grading of lung adenocarcinoma is discussed.
8p vikuala271 13-06-2020 10 2 Download
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The practicing radiologist is continually challenged to update his/her competencies so as to deliver state-of-the-art radiological care. Nowhere is this truer than in the rapidly evolving world of magnetic resonance imaging, where innovations in both technology and diagnostic pharmaceuticals have dramatically altered the landscape of practice.
429p waduroi 03-11-2012 111 19 Download