AIMC Topic: Image Interpretation, Computer-Assisted

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An Unsupervised Learning Tool for Plaque Tissue Characterization in Histopathological Images.

Sensors (Basel, Switzerland) Aug 20, 2024
Stroke is the second leading cause of death and a major cause of disability around the world, and the development of atherosclerotic plaques in the carotid arteries is generally considered the leading cause of severe cerebrovascular events. In recent...
Carotid Arteries Image Processing, Computer-Assisted Plaque, Atherosclerotic Unsupervised Machine Learning Humans Image Interpretation, Computer-Assisted Algorithms
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MASDF-Net: A Multi-Attention Codec Network with Selective and Dynamic Fusion for Skin Lesion Segmentation.

Sensors (Basel, Switzerland) Aug 20, 2024
Automated segmentation algorithms for dermoscopic images serve as effective tools that assist dermatologists in clinical diagnosis. While existing deep learning-based skin lesion segmentation algorithms have achieved certain success, challenges remai...
Image Processing, Computer-Assisted Skin Image Interpretation, Computer-Assisted Dermoscopy Deep Learning Humans Neural Networks, Computer Algorithms
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Deep learning based uterine fibroid detection in ultrasound images.

BMC medical imaging Aug 19, 2024
Uterine fibroids are common benign tumors originating from the uterus's smooth muscle layer, often leading to symptoms such as pelvic pain, and reproductive issues. Early detection is crucial to prevent complications such as infertility or the need f...
Image Interpretation, Computer-Assisted Humans Leiomyoma Deep Learning Ultrasonography Uterine Neoplasms Female Sensitivity and Specificity
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Rethinking masked image modelling for medical image representation.

Medical image analysis Aug 17, 2024
Masked Image Modelling (MIM), a form of self-supervised learning, has garnered significant success in computer vision by improving image representations using unannotated data. Traditional MIMs typically employ a strategy of random sampling across th...
Supervised Machine Learning Image Interpretation, Computer-Assisted Humans Algorithms Image Processing, Computer-Assisted
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An efficient colorectal cancer detection network using atrous convolution with coordinate attention transformer and histopathological images.

Scientific reports Aug 17, 2024
The second most common type of malignant tumor worldwide is colorectal cancer. Histopathology image analysis offers crucial data for the clinical diagnosis of colorectal cancer. Currently, deep learning techniques are applied to enhance cancer classi...
Algorithms Colorectal Neoplasms Deep Learning Humans Image Processing, Computer-Assisted Neural Networks, Computer Image Interpretation, Computer-Assisted
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Harnessing Deep Learning for Accurate Pathological Assessment of Brain Tumor Cell Types.

Journal of imaging informatics in medicine Aug 16, 2024
Primary diffuse central nervous system large B-cell lymphoma (CNS-pDLBCL) and high-grade glioma (HGG) often present similarly, clinically and on imaging, making differentiation challenging. This similarity can complicate pathologists' diagnostic effo...
Lymphoma, Large B-Cell, Diffuse Deep Learning Glioma Humans Neural Networks, Computer Brain Neoplasms Support Vector Machine Image Interpretation, Computer-Assisted
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EAAC-Net: An Efficient Adaptive Attention and Convolution Fusion Network for Skin Lesion Segmentation.

Journal of imaging informatics in medicine Aug 15, 2024
Accurate segmentation of skin lesions in dermoscopic images is of key importance for quantitative analysis of melanoma. Although existing medical image segmentation methods significantly improve skin lesion segmentation, they still have limitations i...
Melanoma Skin Neoplasms Dermoscopy Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Algorithms
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An Automated Machine Learning-Based Quantitative Multiparametric Approach for Mitral Regurgitation Severity Grading.

JACC. Cardiovascular imaging Aug 14, 2024
BACKGROUND: Considering the high prevalence of mitral regurgitation (MR) and the highly subjective, variable MR severity reporting, an automated tool that could screen patients for clinically significant MR (≥ moderate) would streamline the diagnosti...
Mitral Valve Insufficiency Image Interpretation, Computer-Assisted Automation Feasibility Studies Mitral Valve Male Middle Aged Severity of Illness Index Predictive Value of Tests Workflow Female Reproducibility of Results Aged Machine Learning Prognosis Humans
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Computer-Aided Classification of Breast Lesions Based on US RF Time Series Using a Novel Machine Learning Approach.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine Aug 14, 2024
OBJECTIVES: One of the most promising adjuncts for screening breast cancer is ultrasound (US) radio-frequency (RF) time series. It has the superiority of not requiring any supplementary equipment over other methods. This research aimed to propound a ...
Reproducibility of Results Aged Adult Humans Machine Learning Female Breast Breast Neoplasms Image Interpretation, Computer-Assisted Middle Aged Radio Waves Ultrasonography, Mammary
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Multimodal representations of biomedical knowledge from limited training whole slide images and reports using deep learning.

Medical image analysis Aug 14, 2024
The increasing availability of biomedical data creates valuable resources for developing new deep learning algorithms to support experts, especially in domains where collecting large volumes of annotated data is not trivial. Biomedical data include s...
Humans Algorithms Deep Learning Information Storage and Retrieval Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted
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