AIMC Topic: Image Interpretation, Computer-Assisted
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Learnable prototype-guided multiple instance learning for detecting tertiary lymphoid structures in multi-cancer whole-slide pathological images.
Medical image analysis
May 23, 2025
Tertiary lymphoid structures (TLS) are ectopic lymphoid aggregates that form under specific pathological conditions, such as chronic inflammation and malignancies. Their presence within the tumor microenvironment (TME) is strongly correlated with pat...
MSFusion: A multi-source hybrid feature fusion network for accurate grading of invasive breast cancer using H&E-stained histopathological images.
Medical image analysis
May 23, 2025
Invasive breast cancer (IBC) is a prevalent malignant tumor in women, and precise grading plays a pivotal role in ensuring effective treatment and enhancing survival rates. However, accurately grading IBC presents a significant challenge due to its h...
Learning contrast and content representations for synthesizing magnetic resonance image of arbitrary contrast.
Medical image analysis
May 23, 2025
Magnetic Resonance Imaging (MRI) produces images with different contrasts, providing complementary information for clinical diagnoses and research. However, acquiring a complete set of MRI sequences can be challenging due to limitations such as lengt...
Semiautomated segmentation of breast tumor on automatic breast ultrasound image using a large-scale model with customized modules.
Scientific reports
May 19, 2025
To verify the capability of the Segment Anything Model for medical images in 3D (SAM-Med3D), tailored with low-rank adaptation (LoRA) strategies, in segmenting breast tumors in Automated Breast Ultrasound (ABUS) images. This retrospective study colle...
Multi-view hybrid graph convolutional network for volume-to-mesh reconstruction in cardiovascular MRI.
Medical image analysis
May 17, 2025
Cardiovascular magnetic resonance imaging is emerging as a crucial tool to examine cardiac morphology and function. Essential to this endeavour are anatomical 3D surface and volumetric meshes derived from CMR images, which facilitate computational an...
AI-assisted diffuse correlation tomography for identifying breast cancer.
Journal of biomedical optics
May 16, 2025
SIGNIFICANCE: Diffuse correlation tomography (DCT) is an emerging technique for the noninvasive measurement of breast microvascular blood flow, whereas its capability to categorize benign and malignant breast lesions has not been extensively validate...
Deep learning segmentation of periarterial and perivenous capillary-free zones in optical coherence tomography angiography.
Journal of biomedical optics
May 8, 2025
SIGNIFICANCE: Automated segmentation of periarterial and perivenous capillary-free zones (CFZs) in optical coherence tomography angiography (OCTA) can significantly improve early detection and monitoring of diabetic retinopathy (DR), a leading cause ...
Speckle pattern analysis with deep learning for low-cost stroke detection: a phantom-based feasibility study.
Journal of biomedical optics
May 7, 2025
SIGNIFICANCE: Stroke is a leading cause of disability worldwide, necessitating rapid and accurate diagnosis to limit irreversible brain damage. However, many advanced imaging modalities (computerized tomography, magnetic resonance imaging) remain ina...
Unsupervised Test-Time Adaptation for Hepatic Steatosis Grading Using Ultrasound B-Mode Images.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
May 7, 2025
Ultrasound (US) is considered a key modality for the clinical assessment of hepatic steatosis (i.e., fatty liver) due to its noninvasiveness and availability. Deep learning methods have attracted considerable interest in this field, as they are capab...
MedFILIP: Medical Fine-Grained Language-Image Pre-Training.
IEEE journal of biomedical and health informatics
May 6, 2025
Medical vision-language pretraining (VLP) that leverages naturally-paired medical image-report data is crucial for medical image analysis. However, existing methods struggle to accurately characterize associations between images and diseases, leading...
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