Zobrazeno 1 - 10
of 4 024
pro vyhledávání: '"ct images"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract In the field of spinal pathology, sagittal balance of the spine is usually judged by the spatial structure and morphology of pelvis, which can be represented by pelvic parameters. Pelvic parameters, including pelvic incidence, pelvic tilt an
Externí odkaz:
https://doaj.org/article/59f75a0075d3499bbab1af99f42d33cb
Publikováno v:
COVID, Vol 4, Iss 8, Pp 1113-1127 (2024)
The COVID-19 pandemic has spread worldwide for over two years. It was considered a significant threat to global health due to its transmissibility and high pathogenicity. The standard test for COVID-19, namely, reverse transcription polymerase chain
Externí odkaz:
https://doaj.org/article/28fb5f1d46c341519c257be72eb800ed
Autor:
Najmeh Arjmandi, Shahrokh Nasseri, Mehdi Momennezhad, Alireza Mehdizadeh, Sare Hosseini, Shokoufeh Mohebbi, Amin Amiri Tehranizadeh, Zohreh Pishevar
Publikováno v:
Discover Oncology, Vol 15, Iss 1, Pp 1-14 (2024)
Abstract Purpose objective(s) Manual contouring of the prostate region in planning computed tomography (CT) images is a challenging task due to factors such as low contrast in soft tissues, inter- and intra-observer variability, and variations in org
Externí odkaz:
https://doaj.org/article/f3306bf562f742b8ae97dde4573057ea
Publikováno v:
Applied Computer Systems, Vol 29, Iss 1, Pp 112-116 (2024)
Early kidney stone detection is essential for the diagnosis and treatment of people who have kidney stones. The objective of this study is to employ deep learning algorithms for renal stone detection, addressing the critical need for early, accurate
Externí odkaz:
https://doaj.org/article/1c5f6334a9854a43af98d7baae49e672
Autor:
Xiaolei Zhang, M. Iqbal bin Saripan, Yanjun Wu, Zhongxiao Wang, Dong Wen, Zhendong Cao, Bingzhen Wang, Shiqi Xu, Yanli Liu, Mohammad Hamiruce Marhaban, Xianling Dong
Publikováno v:
BMC Medical Imaging, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract Background This study investigated whether the Combat compensation method can remove the variability of radiomic features extracted from different scanners, while also examining its impact on the subsequent predictive performance of machine
Externí odkaz:
https://doaj.org/article/4d8558cc4e2e43c9b0d6406d3aa804b5
Autor:
Ning Yuan, Yongtao Zhang, Kuan Lv, Yiyao Liu, Aocai Yang, Pianpian Hu, Hongwei Yu, Xiaowei Han, Xing Guo, Junfeng Li, Tianfu Wang, Baiying Lei, Guolin Ma
Publikováno v:
Cancer Imaging, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background Accurate segmentation of gastric tumors from CT scans provides useful image information for guiding the diagnosis and treatment of gastric cancer. However, automated gastric tumor segmentation from 3D CT images faces several chall
Externí odkaz:
https://doaj.org/article/108237adcff74acca3a227a0b803313f
Autor:
Hojin Kim, Sang Kyun Yoo, Jin Sung Kim, Yong Tae Kim, Jai Wo Lee, Changhwan Kim, Chae-Seon Hong, Ho Lee, Min Cheol Han, Dong Wook Kim, Se Young Kim, Tae Min Kim, Woo Hyoung Kim, Jayoung Kong, Yong Bae Kim
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract This work aims to investigate the clinical feasibility of deep learning-based synthetic CT images for cervix cancer, comparing them to MR for calculating attenuation (MRCAT). Patient cohort with 50 pairs of T2-weighted MR and CT images from
Externí odkaz:
https://doaj.org/article/4a23c33846da4ec1b3a51cdfd5da32a8
Autor:
Alshamrani K, Alshamrani HA
Publikováno v:
Journal of Multidisciplinary Healthcare, Vol Volume 17, Pp 1459-1472 (2024)
Khalaf Alshamrani,1,2 Hassan A Alshamrani1 1Radiological Sciences Department, Najran University, Najran, Saudi Arabia; 2Department of Oncology and Metabolism, University of Sheffield, Sheffield, UKCorrespondence: Khalaf Alshamrani, Department of Onco
Externí odkaz:
https://doaj.org/article/ca26711d83bc4292b89b03e879008c13
Autor:
Annarita Fanizzi, Annamaria Catino, Samantha Bove, Maria Colomba Comes, Michele Montrone, Angela Sicolo, Rahel Signorile, Pia Perrotti, Pamela Pizzutilo, Domenico Galetta, Raffaella Massafra
Publikováno v:
Frontiers in Oncology, Vol 14 (2024)
IntroductionMalignant pleural mesothelioma (MPM) is a poor-prognosis disease. Owing to the recent availability of new therapeutic options, there is a need to better assess prognosis. The initial clinical response could represent a useful parameter.Me
Externí odkaz:
https://doaj.org/article/3b046e21ce07461792ec79d50f98d1aa
Publikováno v:
Engineering Science and Technology, an International Journal, Vol 56, Iss , Pp 101760- (2024)
Deep learning models based on Transformer and CNN are current research hotspots. However, there are more time complexity and space complexity in extracting global–local features, the feature extraction ability is insufficient for small lesions in C
Externí odkaz:
https://doaj.org/article/6df679784e6b47faaa39bee69bd10658