Duyệt Nguyen Do Trung Chanh, PhD theo Năm xuất bản
Hiển thị tài liệu từ 1-6 của 6
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SEGTRANSVAE: Hybrid CNN-Transformer with Regularization for Medical Image Segmentation
(2022)Current research on deep learning for medical image segmentation highlights limitations in learning either global semantic information or local contextual information effectively. To address these challenges, this paper ... -
CapNext: Unifying Capsule and ResNeXt for Medical Image Segmentation
(2022)Capsule Network is a contemporary approach to image analysis that emphasizes part-whole relationships. However, its applications to segmentation tasks are limited due to training difficulties such as initialization and ... -
Benchmarking saliency methods for chest X-ray interpretation
(2022-08)Saliency methods, which produce heat maps that highlight the areas of the medical image that influence model prediction, are often presented to clinicians as an aid in diagnostic decision-making. However, rigorous investigation ... -
Adaptive Proxy Anchor Loss for Deep Metric Learning
(2022-10)Deep metric learning (or simply called metric learning) uses the deep neural network to learn the representation of images, leading to widely used in many applications, e.g. image retrieval and face recognition. In the ... -
Benchmarking saliency methods for chest X-ray interpretation
(2022-10)Saliency methods, which produce heat maps that highlight the areas of the medical image that influence model prediction, are often presented to clinicians as an aid in diagnostic decision-making. However, rigorous investigation ... -
Wavelet radiomics features from multiphase CT images for screening hepatocellular carcinoma: analysis and comparison
(2023)Early detection of liver malignancy based on medical image analysis plays a crucial role in patient prognosis and personalized treatment. This task, however, is challenging due to several factors, including medical data ...
