Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Joao Santinha"'
Autor:
Nikos Sourlos, Rozemarijn Vliegenthart, Joao Santinha, Michail E. Klontzas, Renato Cuocolo, Merel Huisman, Peter van Ooijen
Publikováno v:
Insights into Imaging, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Various healthcare domains have witnessed successful preliminary implementation of artificial intelligence (AI) solutions, including radiology, though limited generalizability hinders their widespread adoption. Currently, most research group
Externí odkaz:
https://doaj.org/article/7bd1a19456934e9b9fa9aa090ad2aa7d
Autor:
Ana S. C. Verde, Joao Santinha, Eunice Carrasquinha, Nuno Loucao, Ana Gaivao, Jorge Fonseca, Celso Matos, Nikolaos Papanikolaou
Publikováno v:
Insights into Imaging, Vol 11, Iss 1, Pp 1-12 (2020)
Abstract Objectives To study the diffusion tensor-based fiber tracking feasibility to access the male urethral sphincter complex of patients with prostate cancer undergoing Retzius-sparing robot-assisted laparoscopic radical prostatectomy (RS-RARP).
Externí odkaz:
https://doaj.org/article/eaaec127c44b470c8f870262f676fcbc
Publikováno v:
2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA).
Publikováno v:
Journal of Cardiovascular Magnetic Resonance, Vol 26, Iss , Pp 100140- (2024)
Externí odkaz:
https://doaj.org/article/f8bbd5bce403495687a03a3b19ba6c0c
Autor:
Ana Rodrigues, Nuno Rodrigues, João Santinha, Maria V. Lisitskaya, Aycan Uysal, Celso Matos, Inês Domingues, Nickolas Papanikolaou
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-10 (2023)
Abstract There is a growing piece of evidence that artificial intelligence may be helpful in the entire prostate cancer disease continuum. However, building machine learning algorithms robust to inter- and intra-radiologist segmentation variability i
Externí odkaz:
https://doaj.org/article/ef77078ba35a4c9f8f43b4b5dc5f8e1a
Autor:
Sílvia D. Almeida, João Santinha, Francisco P. M. Oliveira, Joana Ip, Maria Lisitskaya, João Lourenço, Aycan Uysal, Celso Matos, Cristina João, Nikolaos Papanikolaou
Publikováno v:
Cancer Imaging, Vol 20, Iss 1, Pp 1-10 (2020)
Abstract Background Whole-body diffusion weighted imaging (WB-DWI) has proven value to detect multiple myeloma (MM) lesions. However, the large volume of imaging data and the presence of numerous lesions makes the reading process challenging. The aim
Externí odkaz:
https://doaj.org/article/9bcb5a155f5c4686ba44f14798e18a5f
Autor:
João Santinha, Linda Bianchini, Mário Figueiredo, Celso Matos, Alessandro Lascialfari, Nikolaos Papanikolaou, Marta Cremonesi, Barbara A. Jereczek-Fossa, Francesca Botta, Daniela Origgi
Publikováno v:
Applied Sciences, Vol 12, Iss 11, p 5465 (2022)
Radiomics is emerging as a promising tool to extract quantitative biomarkers—called radiomic features—from medical images, potentially contributing to the improvement in diagnosis and treatment of oncological patients. However, technical limitati
Externí odkaz:
https://doaj.org/article/dc250dddd4de46bd8ec758ddb07ef004
Autor:
Joao Santinha, Leonardo Martins, Antti Häkkinen, Jason Lloyd-Price, Md, Samuel Oliveira, Abhishekh Gupta, Teppo Annila, Andre Mora, Andre Ribeiro, Fonseca, Jose M.
Publikováno v:
Tampere University
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::592caedf979d86a70f6932d2bc829444
https://researchportal.tuni.fi/en/publications/4c8ae26f-60e0-40e9-b1ca-35f921b35bd8
https://researchportal.tuni.fi/en/publications/4c8ae26f-60e0-40e9-b1ca-35f921b35bd8