AIMC Topic: Image Processing, Computer-Assisted
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Unsupervised single-image super-resolution for infant brain MRI.
NeuroImage
Jun 21, 2025
Acquiring high-resolution (HR) MR images of infant brains is challenging due to lengthy scan times and limited subject compliance. Image super-resolution (SR) techniques can generate HR images from low-resolution (LR) inputs, reducing the need for ex...
Generative deep-learning-model based contrast enhancement for digital subtraction angiography using a text-conditioned image-to-image model.
Computers in biology and medicine
Jun 20, 2025
BACKGROUND: Digital subtraction angiography (DSA) is an essential imaging technique in interventional radiology, enabling detailed visualization of blood vessels by subtracting pre- and post-contrast images. However, reduced contrast, either accident...
BrainTract: segmentation of white matter fiber tractography and analysis of structural connectivity using hybrid convolutional neural network.
Neuroscience
Jun 19, 2025
Tractography uses diffusion Magnetic Resonance Imaging (dMRI) to noninvasively reconstruct brain white matter (WM) tracts, with Convolutional Neural Network (CNNs) like U-Net significantly advancing accuracy in medical image segmentation. This work p...
Deep generative models for Bayesian inference on high-rate sensor data: applications in automotive radar and medical imaging.
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Jun 19, 2025
Deep generative models (DGMs) have been studied and developed primarily in the context of natural images and computer vision. This has spurred the development of (Bayesian) methods that use these generative models for inverse problems in image restor...
Morphological characterization of median nerve and transverse carpal ligament from ultrasound images using convolutional neural networks.
Medical engineering & physics
Jun 18, 2025
OBJECTIVES: The purpose of this study was to automatically segment and quantify the median nerve and carpal arch from ultrasound images using convolutional neural network (CNN).
LoRA-Enhanced RT-DETR: First Low-Rank Adaptation based DETR for real-time full body anatomical structures identification in musculoskeletal ultrasound.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 18, 2025
Medical imaging models for object identification often rely on extensive pretraining data, which is difficult to obtain due to data scarcity and privacy constraints. In practice, hospitals typically have access only to pretrained model weights withou...
Interactive prototype learning and self-learning for few-shot medical image segmentation.
Artificial intelligence in medicine
Jun 18, 2025
Few-shot learning alleviates the heavy dependence of medical image segmentation on large-scale labeled data, but it shows strong performance gaps when dealing with new tasks compared with traditional deep learning. Existing methods mainly learn the c...
Develop intelligent waste bin prototype based on fusion feature recognition of sounds and RGB images.
Waste management (New York, N.Y.)
Jun 18, 2025
Sorting municipal solid waste (MSW) at the source is a critical first step toward achieving a circular economy. Previous research has primarily focused on vision-based intelligent algorithms for MSW classification using red-green-blue (RGB) images. S...
Impact of Field-of-view Zooming and Segmentation Batches on Radiomics Features Reproducibility and Machine Learning Performance in Thyroid Scintigraphy.
Clinical nuclear medicine
Jun 17, 2025
BACKGROUND: Thyroid diseases are the second most common hormonal disorders, necessitating accurate diagnostics. Advances in artificial intelligence and radiomics have enhanced diagnostic precision by analyzing quantitative imaging features. However, ...
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...
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