Quantum-inspired computing may rewrite ultrasound safety rules
A narrative review argues that quantum-inspired algorithms, cloud computing, and edge processors could replace static ultrasound safety indices with dynamic, ...
A narrative review argues that quantum-inspired algorithms, cloud computing, and edge processors could replace static ultrasound safety indices with dynamic, ...
Researchers in Argentina have built a two-stage AI pipeline that generates realistic abdominal ultrasound images from simple semantic label maps, ...
A new deep learning network grades the gain quality of automated breast ultrasound images with 95.49 percent accuracy, outperforming standard ...
Researchers have developed BurnAreaNet, a deep learning system that estimates total body surface area burned from simple 2D masks with ...
A new Transformer-based dual-domain AI framework reconstructs high-quality CT images from sparse projection views, potentially reducing patient radiation exposure while ...
A case-level audit of a public thyroid imaging archive finds contradictory labels, leak-prone data splits, and strong evidence that deep ...
A Danish cohort study of 601 patients finds that MRI without gadolinium-based contrast agents detects intracranial tumors with sensitivity and ...
A Turkish cohort study of 675 children undergoing appendectomy found that ultrasound missed about one in five confirmed appendicitis cases ...
A new systematic review and meta-analysis finds that pre-treatment PET/CT radiomics outperforms post-treatment imaging for predicting pathological complete response in ...
A two-stage neural network fusion system from Romanian researchers achieved 93.53% F1 score in segmenting ovarian tumors from CT scans, ...
A UCLA research team tested whether ChatGPT and Gemini could correctly identify basal cell carcinoma from histologic images, revealing both ...
A University of Texas at Arlington team is developing AI-based 4D reconstruction methods to substantially reduce radiation dose in multi-phase ...
Researchers combined diffusion-generated synthetic retinal images, contrastive self-supervised pre-training, and a five-model ensemble to reach 95.1 percent accuracy in diabetic ...
A new expert-validated dataset provides multi-label artifact annotations for over 20,000 dermoscopic images, exposing the visual noise that undermines AI ...
A YOLOv8-based deep learning model identified and measured children's coronary arteries on echocardiograms with expert-level accuracy in under two seconds ...
Researchers have integrated transformer attention mechanisms into learned primal-dual PET reconstruction, achieving cleaner images from noisy low-count scanner data.
A deep learning model called DROID-RV measures right ventricular size and function from routine echocardiograms and predicts mortality, atrial fibrillation ...
A systematic review of 52 studies finds that artificial intelligence achieves strong technical performance across segmentation, planning, reconstruction, applicator selection, ...
A staged, uncertainty-aware registration framework called PSRR outperformed standard algorithms in 120 water-tank phantom trials, cutting ultrasound-to-CT alignment error by ...
A multicenter study of six radiologists found that a pre-generated GPT-5 checklist and draft report raised binary escalation accuracy on ...
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