AIMC Topic: Image Interpretation, Computer-Assisted

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Transformer attention fusion for fine grained medical image classification.

Scientific reports Jul 1, 2025
Fine-grained visual classification is fundamental for medical image applications because it detects minor lesions. Diabetic retinopathy (DR) is a preventable cause of blindness, which requires exact and timely diagnosis to prevent vision damage. The ...
Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Humans Diabetic Retinopathy
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Deep learning quantifies pathologists' visual patterns for whole slide image diagnosis.

Nature communications Jul 1, 2025
Based on the expertise of pathologists, the pixelwise manual annotation has provided substantial support for training deep learning models of whole slide images (WSI)-assisted diagnostic. However, the collection of pixelwise annotation demands massiv...
Image Processing, Computer-Assisted Pathologists Image Interpretation, Computer-Assisted Humans Deep Learning
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Hybrid transfer learning and self-attention framework for robust MRI-based brain tumor classification.

Scientific reports Jul 1, 2025
Brain tumors are a significant contributor to cancer-related deaths worldwide. Accurate and prompt detection is crucial to reduce mortality rates and improve patient survival prospects. Magnetic Resonance Imaging (MRI) is crucial for diagnosis, but m...
Humans Neural Networks, Computer Brain Neoplasms Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Deep Learning Magnetic Resonance Imaging
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Generative AI for weakly supervised segmentation and downstream classification of brain tumors on MR images.

Scientific reports Jul 1, 2025
Segmenting abnormalities is a leading problem in medical imaging. Using machine learning for segmentation generally requires manually annotated segmentations, demanding extensive time and resources from radiologists. We propose a weakly supervised ap...
Humans Machine Learning Algorithms Image Interpretation, Computer-Assisted Glioma Magnetic Resonance Imaging Supervised Machine Learning Brain Neoplasms Child Image Processing, Computer-Assisted
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Automatic melanoma detection using an optimized five-stream convolutional neural network.

Scientific reports Jul 1, 2025
Melanoma is among the deadliest forms of malignant skin cancer, with the number of cases increasing dramatically worldwide. Its early and accurate diagnosis is crucial for effective treatment. However, automatic melanoma detection has several signifi...
Image Interpretation, Computer-Assisted Deep Learning Convolutional Neural Networks Humans Image Processing, Computer-Assisted Skin Neoplasms Algorithms Neural Networks, Computer Dermoscopy Melanoma
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Deep learning detects retropharyngeal edema on MRI in patients with acute neck infections.

European radiology experimental Jun 19, 2025
BACKGROUND: In acute neck infections, magnetic resonance imaging (MRI) shows retropharyngeal edema (RPE), which is a prognostic imaging biomarker for a severe course of illness. This study aimed to develop a deep learning-based algorithm for the auto...
Image Interpretation, Computer-Assisted Edema Pharyngeal Diseases Neck Magnetic Resonance Imaging Female Acute Disease Aged Young Adult Middle Aged Humans Deep Learning Adult Adolescent Neural Networks, Computer Sensitivity and Specificity Child Male
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Exploratory multi-cohort, multi-reader study on the clinical utility of a deep learning model for transforming cryosectioned to formalin-fixed, paraffin-embedded (FFPE) images in breast lesion diagnosis.

Breast cancer research : BCR Jun 17, 2025
BACKGROUND: Cryosectioned tissues often exhibit artifacts that compromise pathologists' diagnostic accuracy during intraoperative assessments. These inconsistencies, compounded by variations in frozen section (FS) production across laboratories, high...
Cryoultramicrotomy Formaldehyde Deep Learning Humans Cohort Studies Tissue Fixation Breast Image Processing, Computer-Assisted Female Frozen Sections Image Interpretation, Computer-Assisted Breast Neoplasms Paraffin Embedding
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Whole-lesion-aware network based on freehand ultrasound video for breast cancer assessment: a prospective multicenter study.

Cancer imaging : the official publication of the International Cancer Imaging Society Jun 16, 2025
BACKGROUND: The clinical application of artificial intelligence (AI) models based on breast ultrasound static images has been hindered in real-world workflows due to operator-dependence of standardized image acquisition and incomplete view of breast ...
Humans Artificial Intelligence Prospective Studies Retrospective Studies Female Aged Ultrasonography, Mammary Adult Breast Neoplasms Image Interpretation, Computer-Assisted Middle Aged
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FFLUNet: Feature Fused Lightweight UNet for brain tumor segmentation.

Computers in biology and medicine Jun 14, 2025
Brain tumors, particularly glioblastoma multiforme, are considered one of the most threatening types of tumors in neuro-oncology. Segmenting brain tumors is a crucial part of medical imaging. It plays a key role in diagnosing conditions, planning tre...
Humans Brain Neoplasms Magnetic Resonance Imaging Glioblastoma Image Interpretation, Computer-Assisted Deep Learning Software Validation Convolutional Neural Networks Image Processing, Computer-Assisted
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Automated quantification of T1 and T2 relaxation times in liver mpMRI using deep learning: a sequence-adaptive approach.

European radiology experimental Jun 14, 2025
OBJECTIVES: To evaluate a deep learning sequence-adaptive liver multiparametric MRI (mpMRI) assessment with validation in different populations using total and segmental T1 and T2 relaxation time maps.
Multiparametric Magnetic Resonance Imaging Liver Cirrhosis Liver Image Interpretation, Computer-Assisted Algorithms Humans Female Aged Middle Aged Adult Deep Learning Male
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