9 citations · 13 across the 7 of their papers we have counts for
6 papers · 1 filter
ViPSAM: Visual Prompting Medical Image Segmentation Using Segment Anything Model
San Lee, Nalee Kim, Jeong Il Yu +2
In proton therapy planning, respiratory-gated non-contrast CT (NCCT) is commonly used for lesion segmentation; however, accurate delineation remains challenging due to low lesion-t…
Classification of Multi-Parametric Body MRI Series Using Deep Learning
Boah Kim, Tejas Sudharshan Mathai, Kimberly Helm +2
Multi-parametric magnetic resonance imaging (mpMRI) exams have various series types acquired with different imaging protocols. The DICOM headers of these series often have incorrec…
Leveraging Multiphase CT for Quality Enhancement of Portal Venous CT: Utility for Pancreas Segmentation
Xinya Wang, Tejas Sudharshan Mathai, Boah Kim +1
Multiphase CT studies are routinely obtained in clinical practice for diagnosis and management of various diseases, such as cancer. However, the CT studies can be acquired with low…
MRISegmentator-Abdomen: A Fully Automated Multi-Organ and Structure Segmentation Tool for T1-weighted Abdominal MRI
Yan Zhuang, Tejas Sudharshan Mathai, Pritam Mukherjee +6
Background: Segmentation of organs and structures in abdominal MRI is useful for many clinical applications, such as disease diagnosis and radiotherapy. Current approaches have foc…
Automated classification of multi-parametric body MRI series
Boah Kim, Tejas Sudharshan Mathai, Kimberly Helm +1
Multi-parametric MRI (mpMRI) studies are widely available in clinical practice for the diagnosis of various diseases. As the volume of mpMRI exams increases yearly, there are conco…
Automated Classification of Body MRI Sequence Type Using Convolutional Neural Networks
Kimberly Helm, Tejas Sudharshan Mathai, Boah Kim +3
Multi-parametric MRI of the body is routinely acquired for the identification of abnormalities and diagnosis of diseases. However, a standard naming convention for the MRI protocol…