7 papers
Effectiveness of Automatically Curated Dataset in Thyroid Nodules Classification Algorithms Using Deep Learning
Jichen Yang, Jikai Zhang, Benjamin Wildman-Tobriner +1
The diagnosis of thyroid nodule cancers commonly utilizes ultrasound images. Several studies showed that deep learning algorithms designed to classify benign and malignant thyroid…
Diagnostic Impact of Cine Clips for Thyroid Nodule Assessment on Ultrasound
Jichen Yang, Brian C. Allen, Kirti Magudia +4
Background: Thyroid ultrasound is commonly performed using a combination of static images and cine clips (video recordings). However, the exact utility and impact of cine images re…
Automated Muscle and Fat Segmentation in Computed Tomography for Comprehensive Body Composition Analysis
Yaqian Chen, Hanxue Gu, Yuwen Chen +7
Body composition assessment using CT images can potentially be used for a number of clinical applications, including the prognostication of cardiovascular outcomes, evaluation of m…
BreastSegNet: Multi-label Segmentation of Breast MRI
Qihang Li, Jichen Yang, Yaqian Chen +4
Breast MRI provides high-resolution imaging critical for breast cancer screening and preoperative staging. However, existing segmentation methods for breast MRI remain limited in s…
SegmentAnyMuscle: A universal muscle segmentation model across different locations in MRI
Roy Colglazier, Jisoo Lee, Haoyu Dong +12
The quantity and quality of muscles are increasingly recognized as important predictors of health outcomes. While MRI offers a valuable modality for such assessments, obtaining pre…
How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model
Hanxue Gu, Haoyu Dong, Jichen Yang +1
Automated segmentation is a fundamental medical image analysis task, which enjoys significant advances due to the advent of deep learning. While foundation models have been useful…