This paper addresses the automated segmentation of multiple organs in upper abdominal computed tomography (CT) data. The aim of our study is to develop methods to effectively construct the conditional priors and use their prediction power for more ac...
Abdominal segmentation on clinically acquired computed tomography (CT) has been a challenging problem given the inter-subject variance of human abdomens and complex 3-D relationships among organs. Multi-atlas segmentation (MAS) provides a potentially...
OBJECTIVE: To standardize and objectivize treatment response assessment in oncology, guidelines have been proposed that are driven by radiological measurements, which are typically communicated in free-text reports defying automated processing. We st...
RATIONALE AND OBJECTIVES: We aimed to compare the capabilities of two leading large language models (LLMs), GPT-4 and Gemini, in analyzing serial radiology reports, to highlight oncological issues that require further clinical attention.
OBJECTIVES: To evaluate the effectiveness of super-resolution deep learning reconstruction (SR-DLR) in low-dose abdominal computed tomography (CT) imaging compared with hybrid iterative reconstruction (HIR) and conventional deep learning reconstructi...
OBJECTIVE: To develop a deep learning algorithm for diagnosing lumbar central canal stenosis (LCCS) using abdominal CT (ACT) and lumbar spine CT (LCT).
We created and validated an open-access AI algorithm (AIc) for assessing image segmentation and patient centering in a multi-body-region, multi-center, and multi-scanner study. Our study included 825 head, chest, and abdomen-pelvis CT from 275 patien...
Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
Mar 1, 2025
In small animal practice, patients often present with urinary lithiasis, and prediction of urolith composition is essential to determine the appropriate treatment. Through abdominal radiographs, the composition of mineral radiopaque uroliths can be d...
Journal of the American College of Radiology : JACR
Mar 1, 2025
BACKGROUND: Prekidney transplant evaluation routinely includes abdominal CT for presurgical vascular assessment. A wealth of body composition data are available from these CT examinations, but they remain an underused source of data, often missing fr...
Radiographics : a review publication of the Radiological Society of North America, Inc
Dec 1, 2024
The implementation of deep neural networks has spurred the creation of deep learning reconstruction (DLR) CT algorithms. DLR CT techniques encompass a spectrum of deep learning-based methodologies that operate during the different steps of the image ...
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