AIMC Topic: Image Interpretation, Computer-Assisted
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Review on computational methods for the detection and classification of Parkinson's Disease.
Computers in biology and medicine
Feb 11, 2025
BACKGROUND AND OBJECTIVE: The worldwide estimates reveal two-fold increase in incidence of Parkinson's disease (PD) over 25 years. The two-fold increased incidence and lack of proper treatment uplifted a compelling solicitude, nagging towards accurat...
Multi-modality medical image classification with ResoMergeNet for cataract, lung cancer, and breast cancer diagnosis.
Computers in biology and medicine
Feb 11, 2025
The variability in image modalities presents significant challenges in medical image classification, as traditional deep learning models often struggle to adapt to different image types, leading to suboptimal performance across diverse datasets. This...
Use of deep learning-accelerated T2 TSE for prostate MRI: Comparison with and without hyoscine butylbromide admission.
Magnetic resonance imaging
Feb 10, 2025
OBJECTIVE: To investigate the use of deep learning (DL) T2-weighted turbo spin echo (TSE) imaging sequence with deep learning acceleration (T2DL) in prostate MRI regarding the necessity of hyoscine butylbromide (HBB) administration for high image qua...
EDSRNet: An Enhanced Decoder Semantic Recovery Network for 2D Medical Image Segmentation.
IEEE journal of biomedical and health informatics
Feb 10, 2025
In recent years, with the advancement of medical imaging technology, medical image segmentation has played a key role in assisting diagnosis and treatment planning. Current deep learning-based medical image segmentation methods mainly adopt encoder-d...
PFPRNet: A Phase-Wise Feature Pyramid With Retention Network for Polyp Segmentation.
IEEE journal of biomedical and health informatics
Feb 10, 2025
Early detection of colonic polyps is crucial for the prevention and diagnosis of colorectal cancer. Currently, deep learning-based polyp segmentation methods have become mainstream and achieved remarkable results. Acquiring a large number of labeled ...
M-NET: Transforming Single Nucleotide Variations Into Patient Feature Images for the Prediction of Prostate Cancer Metastasis and Identification of Significant Pathways.
IEEE journal of biomedical and health informatics
Feb 10, 2025
High-performance prediction of prostate cancer metastasis based on single nucleotide variations remains a challenge. Therefore, we developed a novel biologically informed deep learning framework, named M-NET, for the prediction of prostate cancer met...
ContraSurv: Enhancing Prognostic Assessment of Medical Images via Data-Efficient Weakly Supervised Contrastive Learning.
IEEE journal of biomedical and health informatics
Feb 10, 2025
Prognostic assessment remains a critical challenge in medical research, often limited by the lack of well-labeled data. In this work, we introduce ContraSurv, a weakly-supervised learning framework based on contrastive learning, designed to enhance p...
Using deep feature distances for evaluating the perceptual quality of MR image reconstructions.
Magnetic resonance in medicine
Feb 8, 2025
PURPOSE: Commonly used MR image quality (IQ) metrics have poor concordance with radiologist-perceived diagnostic IQ. Here, we develop and explore deep feature distances (DFDs)-distances computed in a lower-dimensional feature space encoded by a convo...
A novel deep learning framework for retinal disease detection leveraging contextual and local features cues from retinal images.
Medical & biological engineering & computing
Feb 7, 2025
Retinal diseases are a serious global threat to human vision, and early identification is essential for effective prevention and treatment. However, current diagnostic methods rely on manual analysis of fundus images, which heavily depends on the exp...
A comprehensive analysis of deep learning and transfer learning techniques for skin cancer classification.
Scientific reports
Feb 7, 2025
Accurately and early diagnosis of melanoma is one of the challenging tasks due to its unique characteristics and different shapes of skin lesions. So, in order to solve this issue, the current study examines various deep learning-based approaches and...
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