6 citations · 14 across the 5 of their papers we have counts for
6 papers · 1 filter
CopilotCAD: Empowering Radiologists with Report Completion Models and Quantitative Evidence from Medical Image Foundation Models
Sheng Wang, Tianming Du, Katherine Fischer +5
Computer-aided diagnosis systems hold great promise to aid radiologists and clinicians in radiological clinical practice and enhance diagnostic accuracy and efficiency. However, th…
From Single-Visit to Multi-Visit Image-Based Models: Single-Visit Models are Enough to Predict Obstructive Hydronephrosis
Stanley Bryan Z. Hua, Mandy Rickard, John Weaver +8
Previous work has shown the potential of deep learning to predict renal obstruction using kidney ultrasound images. However, these image-based classifiers have been trained with th…
Fully-automatic segmentation of kidneys in clinical ultrasound images using a boundary distance regression network
Shi Yin, Zhengqiang Zhang, Hongming Li +5
It remains challenging to automatically segment kidneys in clinical ultrasound images due to the kidneys' varied shapes and image intensity distributions, although semi-automatic m…
Automatic kidney segmentation in ultrasound images using subsequent boundary distance regression and pixelwise classification networks
Shi Yin, Qinmu Peng, Hongming Li +5
It remains challenging to automatically segment kidneys in clinical ultrasound (US) images due to the kidneys' varied shapes and image intensity distributions, although semi-automa…
Transfer learning for diagnosis of congenital abnormalities of the kidney and urinary tract in children based on Ultrasound imaging data
Qiang Zheng, Gregory Tasian, Yong Fan
Classification of ultrasound (US) kidney images for diagnosis of congenital abnormalities of the kidney and urinary tract (CAKUT) in children is a challenging task. It is desirable…
A dynamic graph-cuts method with integrated multiple feature maps for segmenting kidneys in ultrasound images
Qiang Zheng, Steven Warner, Gregory Tasian +1
Purpose: To improve kidney segmentation in clinical ultrasound (US) images, we develop a new graph cuts based method to segment kidney US images by integrating original image inten…