Disentangle Then Calibrate With Gradient Guidance: A Unified Framework for Common and Rare Disease Diagnosis-Reference-Cited by-同舟云学术

Disentangle Then Calibrate With Gradient Guidance: A Unified Framework for Common and Rare Disease Diagnosis

Published:2024-05 Issue:5 Volume:43 Page:1816-1827
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Chen Yuanyuan¹^ORCID,Guo Xiaoqing²,Xia Yong¹^ORCID,Yuan Yixuan³^ORCID

Affiliation:

1. National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an, China

2. Department of Engineering Science, University of Oxford, Oxford, U.K

3. Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, SAR, China

Funder

National Natural Science Foundation of China

Ningbo Clinical Research Center for Medical Imaging

Open Project

National Key Research and Development Program of China

Hong Kong Research Grants Council General Research Fund

Innovation and Technology Commission-Innovation and Technology Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/42/10517791/10379649.pdf?arnumber=10379649

Reference49 articles.

1. Learn to Threshold: ThresholdNet With Confidence-Guided Manifold Mixup for Polyp Segmentation

2. Iterative sparse and deep learning for accurate diagnosis of Alzheimer’s disease

3. Disease-image-specific Learning for Diagnosis-oriented Neuroimage Synthesis with Incomplete Multi-Modality Data

4. Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification

5. Deep Lesion Tracker: Monitoring Lesions in 4D Longitudinal Imaging Studies

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