BACKGROUND: Magnetic Resonance (MR) imaging is the preferred modality for staging in rectal cancer; however, despite its exceptional soft tissue contrast, segmenting rectal tumors on MR images remains challenging due to the overlapping appearance of ...
OBJECTIVE: To evaluate whether deep learning (DL) analysis of intratumor subregion based on dynamic contrast-enhanced MRI (DCE-MRI) can help predict Ki-67 expression level in breast cancer.
The international journal of cardiovascular imaging
Mar 13, 2025
Right ventricular (RV) end-diastolic volume (RVEDV) and ejection fraction (RVEF) by cardiac MRI (cMRI) guide management in chronic pulmonary regurgitation (PR). Two-dimensional echocardiography suboptimally correlate with RV volumes. This study teste...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 12, 2025
Artificial intelligence (AI) has shown great promise in analyzing nasal endoscopic images for disease detection. However, current AI systems require extensive expert-labeled data for each specific medical condition, limiting their applications. In th...
OBJECTIVE: Scoliosis, a 3-D spinal deformity, requires early detection and intervention. Ultrasound curve angle (UCA) measurement using ultrasound images has emerged as a promising diagnostic tool. However, calculating the UCA directly from ultrasoun...
Histopathological image classification using deep learning is crucial for accurate and efficient cancer diagnosis. However, annotating a large amount of histopathological images for training is costly and time-consuming, leading to a scarcity of avai...
OBJECTIVES: To develop an automated deep learning (DL) methodology for detecting small hepatocellular carcinoma (sHCC) in cirrhotic livers, leveraging Gd-EOB-DTPA-enhanced MRI.
Accurate and timely classification of skin diseases is essential for effective dermatological diagnosis. However, the limited availability of annotated images, particularly for rare or novel conditions, poses a significant challenge. Although few-sho...
OBJECTIVES: This study investigated the impact of human-large language model (LLM) collaboration on the accuracy and efficiency of brain MRI differential diagnosis.
This special report explores the integration of artificial intelligence (AI) into prostate MRI workflows to address limitations associated with single-reader interpretations, such as inter-reader variability and diagnostic errors. We review various A...
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