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Articles by Yipeng Hu
Development and validation of a versatile foundation model for cine cardiac magnetic resonance image analysis
Abstract Cardiac magnetic resonance imaging is central to cardiovascular diagnosis and management, yet extracting key clinical measurements remains time-consuming, subjective, and of limited reproducibility. Current deep learning methods often require a separate model trained from scratch for each task, and generating sufficient labelled training data demands substantial clinical expertise.
A computationally frugal, open-source chest CT foundation model for thoracic disease detection in lung cancer screening programmes - Communications Medicine
Abstract Low-dose computed tomography (LDCT) employed in lung cancer screening (LCS) programmes is increasing in uptake worldwide. LCS programmes herald a generational opportunity to simultaneously detect cancer and non-cancer-related early-stage lung disease, yet these efforts are hampered by a shortage of radiologists to interpret scans at scale. Here, we present TANGERINE, a computationally frugal, open-source vision foundation model for volumetric LDCT analysis.
Quantitative analysis of uterine peristalsis on transvaginal sonography in women with adenomyosis using optical flow for motion quantification: inter- and intra-observer reproducibility study
Keywords Adenomyosis assisted conception infertility uterine peristalsis optical flow Adenomyosis can adversely reduce the chance of pregnancy in women undergoing assisted conception, with altered uterine peristalsis proposed as a mechanism. The proposed approach for wave motion quantification offers an objective and reproducible measuring tool to quantify uterine peristalsis on transvaginal sonography.
Effects on Iron Metabolism and System Xc-/GPX4 Pathway from Hydroquinone Suggest Ferroptosis of Jurkat Cells
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[2303.06040] Importance of Aligning Training Strategy with Evaluation for Diffusion Models in 3D Multiclass Segmentation
[Submitted on 10 Mar 2023 ( v1 ), last revised 18 Aug 2023 (this version, v3)] Title:Importance of Aligning Training Strategy with Evaluation for Diffusion Models in 3D Multiclass Segmentation Download a PDF of the paper titled Importance of Aligning Training Strategy with Evaluation for Diffusion Models in 3D Multiclass Segmentation, by Yunguan Fu and Yiwen Li and Shaheer U. Saeed and Matthew J.
False Positive Multiparametric Magnetic Resonance Imaging Phenotypes in the Biopsy-naïve Prostate: Are They Distinct from Significant Cancer-associated Lesions? Lessons from PROMIS
Abstract Background False positive multiparametric magnetic resonance imaging (mpMRI) phenotypes prompt unnecessary biopsies. The Prostate MRI Imaging Study (PROMIS) provides a unique opportunity to explore such phenotypes in biopsy-naïve men with raised prostate-specific antigen (PSA) and suspected cancer. Objective To compare mpMRI lesions in men with/without significant cancer on transperineal mapping biopsy (TPM).
The SmartTarget Biopsy Trial: A Prospective, Within-person Randomised, Blinded Trial Comparing the Accuracy of Visual-registration and Magnetic Resonance Imaging/Ultrasound Image-fusion Targeted Biopsies for Prostate Cancer Risk Stratification
1. Introduction Current management strategies for prostate cancer (PC) depend heavily on appropriate risk stratification, for which adequate tumour sampling and localisation are pivotal. The standard 12-core systematic transrectal ultrasound (TRUS)-guided prostate biopsy has, however, led to overdiagnosis of indolent cancers in some patients and undersampling in others.
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