Výsledky vyhledávání - "multi-parametric magnetic resonance imaging"

Akademický článek

Investigation of the Effectiveness of Prostate Biopsy Density in Predicting Prostate Cancer Under Cognitive and Systematic Biopsy in Multi-Parametric Magnetic Resonance Imaging (mpMRI)

Autor: Feng J, Chen K, Tian H, Abdulkarem AQM, Tuo Y, Wang X, Huang B, Gao Y, Lv Z, He R, Li G

Publikováno v: Cancer Management and Research, Vol Volume 16, Pp 883-890 (2024)

Jiajin Feng,1,* Keming Chen,1,* Haifu Tian,1 Al-qaisi Mohammed Abdulkarem,1 Yunshang Tuo,1 Xuehao Wang,1 Bincheng Huang,1 Yu Gao,1 Zhiyong Lv,1 Rui He,2 Guangyong Li1 1General Hospital of Ningxia Medical University, Yinchuan, 750004, People�

Externí odkaz: https://doaj.org/article/1b16e8beadb043899357c62d99bff524

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Akademický článek

Prediction of breast cancer and axillary positive-node response to neoadjuvant chemotherapy based on multi-parametric magnetic resonance imaging radiomics models

Autor: Yingyu Lin, Jifei Wang, Meizhi Li, Chunxiang Zhou, Yangling Hu, Mengyi Wang, Xiaoling Zhang

Publikováno v: Breast, Vol 76, Iss , Pp 103737- (2024)

Purpose: Accurate identification of primary breast cancer and axillary positive-node response to neoadjuvant chemotherapy (NAC) is important for determining appropriate surgery strategies. We aimed to develop combining models based on breast multi-pa

Externí odkaz: https://doaj.org/article/ccf3474cd7b24bf2aecd9c93a7f41ccd

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Akademický článek

Preoperative Molecular Subtype Classification Prediction of Ovarian Cancer Based on Multi-Parametric Magnetic Resonance Imaging Multi-Sequence Feature Fusion Network

Autor: Yijiang Du, Tingting Wang, Linhao Qu, Haiming Li, Qinhao Guo, Haoran Wang, Xinyuan Liu, Xiaohua Wu, Zhijian Song

Publikováno v: Bioengineering, Vol 11, Iss 5, p 472 (2024)

In the study of the deep learning classification of medical images, deep learning models are applied to analyze images, aiming to achieve the goals of assisting diagnosis and preoperative assessment. Currently, most research classifies and predicts n

Externí odkaz: https://doaj.org/article/12f0787dad134ce582f4c67207c2ecdb

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Akademický článek

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Vesical imaging reporting and data system (VI-RADS), a new modality in bladder cancer treatment

Autor: Tomica Bratić, Mirta Zaken-Vučetić, Filip Brkić, Vittorio Perić, Maja Grubelić-Crnčević, Gordana Lovrečić-Prpić, Saša Schmidt

Publikováno v: Libri Oncologici, Vol 50, Iss 1, Pp 27-31 (2022)

Bladder carcinoma incidence is on the rise making it the tenth most common and thirteenth deadliest carcinoma in the world. Transurethral resection of bladder tumor (TURBT) following a cystoscopy is the golden standard for diagnosis and treatment, de

Externí odkaz: https://doaj.org/article/7d2ae90fa67949258991a978565ca7a7

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Akademický článek

Pilot study for generating and assessing nomograms and decision curves analysis to predict clinically significant prostate cancer using only spatially registered multi-parametric MRI

Autor: Rulon Mayer, Baris Turkbey, Peter Choyke, Charles B. Simone

Publikováno v: Frontiers in Oncology, Vol 13 (2023)

BackgroundCurrent prostate cancer evaluation can be inaccurate and burdensome. To help non-invasive prostate tumor assessment, recent algorithms applied to spatially registered multi-parametric (SRMP) MRI extracted novel clinically relevant metrics,

Externí odkaz: https://doaj.org/article/b66370c8d2e747e6bcf27fe1a84d6623

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Akademický článek

Histogram analysis of diffusion-weighted magnetic resonance imaging as a biomarker to predict LNM in T3 stage rectal carcinoma

Autor: Yang Zhou, Rui Yang, Yuan Wang, Meng Zhou, Xueyan Zhou, JiQing Xing, Xinxin Wang, Chunhui Zhang

Publikováno v: BMC Medical Imaging, Vol 21, Iss 1, Pp 1-10 (2021)

Abstract Background Preoperative identification of rectal cancer lymph node status is crucial for patient prognosis and treatment decisions. Rectal magnetic resonance imaging (MRI) plays an essential role in the preoperative staging of rectal cancer,

Externí odkaz: https://doaj.org/article/60415aec794745b3805204f84b4a08a1

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Akademický článek

Identifying Risk Factors for MRI-Invisible Prostate Cancer in Patients Undergoing Transperineal Saturation Biopsy

Autor: Artiles Medina A, Rodríguez-Patrón Rodríguez R, Ruiz Hernández M, Mata Alcaraz M, García Barreras S, Fernández Conejo G, Fraile Poblador A, Sanz Mayayo E, Burgos Revilla FJ

Publikováno v: Research and Reports in Urology, Vol Volume 13, Pp 723-731 (2021)

Alberto Artiles Medina, Rafael Rodríguez-Patrón Rodríguez, Mercedes Ruiz Hernández, Marina Mata Alcaraz, Silvia García Barreras, Guillermo Fernández Conejo, Agustín Fraile Poblador, Enrique Sanz Mayayo, Francisco Javier Burgos Revilla Departme

Externí odkaz: https://doaj.org/article/f51c3cb3c39f427881260df58c692bbd

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Computer-aided diagnosis of prostate cancer based on deep neural networks from multi-parametric magnetic resonance imaging

Autor: Zhenglin Yi, Zhenyu Ou, Jiao Hu, Dongxu Qiu, Chao Quan, Belaydi Othmane, Yongjie Wang, Longxiang Wu

Publikováno v: Frontiers in Physiology, Vol 13 (2022)

Objectives: To evaluate a new deep neural network (DNN)–based computer-aided diagnosis (CAD) method, namely, a prostate cancer localization network and an integrated multi-modal classification network, to automatically localize prostate cancer on m

Externí odkaz: https://doaj.org/article/5edab2e652444f0ab5df95d4fdb275c2

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