Pengyi Xing

Biparametric MRI in prostate cancer: utility of whole-prostate and whole-lesion histogram and texture analysis for clinically significant prostate cancer

Luguang Chen, Pengyi Xing, Tiegong Wang, Xiaoyu Huang et autres

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Improved prostate cancer diagnosis: upgraded prostate imaging reporting and data system (PI-RADS) scores by zoomed diffusion-weighted imaging enhance deep-learning-based computer-aided diagnosis accuracy

Haining Long, Lei Hu, Liming Wei, Lisong Dai et autres

Background: A new diffusion-weighted imaging (DWI) technique, known as zoomed-field-of-view echo-planar DWI (z-DWI), has been developed to reduce geometric distortions and susceptibility artifacts and to achieve higher spatial resolution. However, it remains unclear whether z-DWI, compared with the traditional DWI technique, can …

cn, de, us, nl, kr, ch, at, pl (code pays fourni par la source)

Improving PI-RADS rating with Zoomed Diffusion-Weighted Imaging in Deep Learning CAD Systems

Haining Long, W.P. Zhu, Lei Hu, Liming Wei et autres

Motivation: The clinical accuracy of the Prostate Imaging Reporting and Data System (PI-RADS) rating by deep-learning-based computer-aided diagnosis (DL-CAD) models need further enhancement for improved prostate cancer (PCa) detection and fewer unnecessary biopsies. Goal(s): This study aimed to achieve more precise PI-RADS …

A deep learning algorithm that aids visualization of femoral neck fractures and improves physician training

Pengyi Xing, Li Zhang, Tiegong Wang, Lipeng Wang et autres

cn (code pays fourni par la source)

Automated deep-learning system in the assessment of MRI-visible prostate cancer: comparison of advanced zoomed diffusion-weighted imaging and conventional technique

Lei Hu, Caixia Fu, Xinyang Song, Robert Grimm et autres

Abstract Background Deep-learning-based computer-aided diagnosis (DL-CAD) systems using MRI for prostate cancer (PCa) detection have demonstrated good performance. Nevertheless, DL-CAD systems are vulnerable to high heterogeneities in DWI, which can interfere with DL-CAD assessments and impair performance. This study aims to compare …

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A concurrent, deep learning–based computer-aided detection system for prostate multiparametric MRI: a performance study involving experienced and less-experienced radiologists

Sandra Labus, M. Altmann, Henkjan Huisman, Angela Tong et autres

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Prediction of clinically significant prostate cancer with a multimodal MRI-based radiomics nomogram

Guodong Jing, Pengyi Xing, Zhihui Li, Xiaolu Ma et autres

Objective To develop and validate a multimodal MRI-based radiomics nomogram for predicting clinically significant prostate cancer (CS-PCa). Methods Patients who underwent radical prostatectomy with pre-biopsy prostate MRI in three different centers were assessed retrospectively. Totally 141 and 60 cases were included in …

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Differentiating prostate cancer from benign prostatic hyperplasia using whole-lesion histogram and texture analysis of diffusion- and T2-weighted imaging

Pengyi Xing, Luguang Chen, Qingsong Yang, Tao Song et autres

Abstract Background To explore the usefulness of analyzing histograms and textures of apparent diffusion coefficient (ADC) maps and T2-weighted (T2W) images to differentiate prostatic cancer (PCa) from benign prostatic hyperplasia (BPH) using histopathology as the reference. Methods Ninety patients with PCa and …

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Detection and PI-RADS classification of focal lesions in prostate MRI: Performance comparison between a deep learning-based algorithm (DLA) and radiologists with various levels of experience

Seo Yeon Youn, Moon Hyung Choi, Dong Hwan Kim, Young Joon Lee et autres

kr, us, nl, de, fr, ch, cn, at (code pays fourni par la source)

Noncontrast Magnetic Resonance Radiomics and Multilayer Perceptron Network Classifier: An approach for Predicting Fibroblast Activation Protein Expression in Patients With Pancreatic Ductal Adenocarcinoma

Yinghao Meng, Hao Zhang, Qi Li, Pengyi Xing et autres

BACKGROUND: Fibroblast activation protein (FAP) in pancreatic ductal adenocarcinoma (PDAC) is closely related to the prognosis and treatment of patients. Accurate preoperative FAP expression can better identify the population benefitting from FAP-targeting drugs. PURPOSE: To develop and validate a machine learning classifier …

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Knockdown of lncRNA MIR4435‑2HG and ST8SIA1 expression inhibits the proliferation, invasion and migration of prostate cancer cells in vitro and in vivo by blocking the activation of the FAK/AKT/β‑catenin signaling pathway

Pengyi Xing, Ye Wang, Li Zhang, Chao Ma et autres

Prostate cancer is a main health risk for males with a high incidence and mortality. The present study aimed to examine the effects of long non‑coding RNA (lncRNA) MIR4435‑2HG binding with ST8SIA1 on the proliferation, invasion and migration of prostate cancer cells …

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A Novel Deep Learning Based Computer-Aided Diagnosis System Improves the Accuracy and Efficiency of Radiologists in Reading Biparametric Magnetic Resonance Images of the Prostate

David Winkel, Angela Tong, Bin Lou, Ali Kamen et autres

OBJECTIVE: The aim of this study was to evaluate the effect of a deep learning based computer-aided diagnosis (DL-CAD) system on radiologists' interpretation accuracy and efficiency in reading biparametric prostate magnetic resonance imaging scans. MATERIALS AND METHODS: We selected 100 consecutive prostate …

ch, us, gb, nl, at, kr, cn, de (code pays fourni par la source)