AIMC Topic:
Image Interpretation, Computer-Assisted
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Exploring Unbiased Activation Maps for Weakly Supervised Tissue Segmentation of Histopathological Images.
IEEE transactions on medical imaging
Jun 1, 2025
Tissue segmentation in histopathological images plays a crucial role in computational pathology, owing to its significant potential to indicate the prognosis of cancer patients. Presently, numerous Weakly Supervised Semantic Segmentation (WSSS) metho...
FeaInfNet: Diagnosis of Medical Images With Feature-Driven Inference and Visual Explanations.
IEEE journal of biomedical and health informatics
Jun 1, 2025
Interpretable deep-learning models have received widespread attention in the field of image recognition. However, owing to the coexistence of medical-image categories and the challenge of identifying subtle decision-making regions, many proposed inte...
Boundary-Enhanced $U^{2}$-Net for Simultaneous Four-Chamber Segmentation in Transthoracic Echocardiography.
IEEE journal of biomedical and health informatics
Jun 1, 2025
The heart, responsible for circulating blood throughout our body, contains four chambers. Existing analysis methods primarily focus on one single ventricle. Transthoracic echocardiography provides real-time estimations of cardiac function and enables...
Coarse for Fine: Bounding Box Supervised Thyroid Ultrasound Image Segmentation Using Spatial Arrangement and Hierarchical Prediction Consistency.
IEEE journal of biomedical and health informatics
Jun 1, 2025
Weakly-supervised learning methods have become increasingly attractive for medical image segmentation, but suffered from a high dependence on quantifying the pixel-wise affinities of low-level features, which are easily corrupted in thyroid ultrasoun...
Enhancing Medical Vision-Language Contrastive Learning via Inter-Matching Relation Modeling.
IEEE transactions on medical imaging
Jun 1, 2025
Medical image representations can be learned through medical vision-language contrastive learning (mVLCL) where medical imaging reports are used as weak supervision through image-text alignment. These learned image representations can be transferred ...
FedBCD: Federated Ultrasound Video and Image Joint Learning for Breast Cancer Diagnosis.
IEEE transactions on medical imaging
Jun 1, 2025
Ultrasonography plays an essential role in breast cancer diagnosis. Current deep learning based studies train the models on either images or videos in a centralized learning manner, lacking consideration of joint benefits between two different modali...
Hierarchical Multi-Class Group Correlation Learning Network for Medical Image Segmentation.
IEEE journal of biomedical and health informatics
Jun 1, 2025
Hierarchical approaches have been tremendously successful at multi-label segmentation. However, it has been shown they may seriously suffer from the problem of only imposing constraints on shallow layers while ignoring deep relationships in the label...
Automated Ensemble Multimodal Machine Learning for Healthcare.
IEEE journal of biomedical and health informatics
Jun 1, 2025
The application of machine learning in medicine and healthcare has led to the creation of numerous diagnostic and prognostic models. However, despite their success, current approaches generally issue predictions using data from a single modality. Thi...
TGAP-Net: Twin Graph Attention Pseudo-Label Generation for Weakly Supervised Semantic Segmentation.
IEEE journal of biomedical and health informatics
Jun 1, 2025
Multilabel pathological tissue segmentation is a vital task in computational pathology that aims to semantically segment different tissues within pathological images. Fully and weakly supervised models have demonstrated impressive performances in thi...
Modality-Aware Distillation Network for Microvascular Invasion Prediction of Hepatocellar Carcinoma From MRI Images.
IEEE transactions on bio-medical engineering
Jun 1, 2025
Microvascular invasion (MVI) of hepatocellular carcinoma (HCC) is a crucial histopathologic prognostic factor associated with cancer recurrence after liver transplantation or hepatectomy. Recently, clinicoradiologic characteristics are combined with ...
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