Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Felix Lades"'
Autor:
Moritz T. Winkelmann, Sebastian Gassenmaier, Sven S. Walter, Christoph Artzner, Felix Lades, Sebastian Faby, Konstantin Nikolaou, Malte N. Bongers
Publikováno v:
Diagnostic and Interventional Radiology, Vol 28, Iss 3, Pp 208-216 (2022)
PURPOSEDifferentiation of incidental adrenal lesions remains a challenge in diagnostic imaging, especially on single-phase portal venous computed tomography (CT) in the oncological setting. The aim of the study was to explore the ability of dual-ener
Externí odkaz:
https://doaj.org/article/c4085e5fd4b746f89abe6672fbe9e1f8
Autor:
Ming He, Xinyue Chen, Michael Wels, Felix Lades, Yatong Li, Zaiyi Liu, Zhengyu Jin, Huadan Xue
Publikováno v:
Academic Radiology. 30:680-688
To develop and validate an effective model for identifying patients with postoperative local disease recurrence of pancreatic ductal adenocarcinoma (PDAC).A total of 153 patients who had undergone surgical resection of PDAC with regular postoperative
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::69a8ba78df55a1e0faaca2ddfeaef58a
https://doi.org/10.1016/j.acra.2022.05.019
https://doi.org/10.1016/j.acra.2022.05.019
Autor:
Martin Sedlmair, Mannudeep K. Kalra, Bernhard Schmidt, Felix Lades, Fatemeh Homayounieh, Chayanin Nitiwarangkul, Sanjay Saini, Ramandeep Singh
Publikováno v:
American Journal of Roentgenology. 215:398-405
OBJECTIVE. This study assessed a machine learning-based dual-energy CT (DECT) tumor analysis prototype for semiautomatic segmentation and radiomic analysis of benign and malignant liver lesions seen on contrast-enhanced DECT. MATERIALS AND METHODS. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f69c65a684f9574fdf791bc47714f1e3
https://doi.org/10.2214/ajr.19.22164
https://doi.org/10.2214/ajr.19.22164
Autor:
Alexander Mühlberg, Rainer Kärgel, Alexander Katzmann, Michael Sühling, Volker Heinemann, Stefan Maurus, Oliver Taubmann, Martine Remy-Jardin, Felix Lades, Julian Walter Holch, Thomas Huber, Jean-Baptiste Faivre, Michael Wels, Dominik Nörenberg
Publikováno v:
Scientific Reports, Vol 10, Iss 1, Pp 1-15 (2020)
Scientific Reports
Scientific Reports
The goal of radiomics is to convert medical images into a minable data space by extraction of quantitative imaging features for clinically relevant analyses, e.g. survival time prediction of a patient. One problem of radiomics from computed tomograph
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::653b48ff30f0c84b64a3cfd736bf7c6d
http://link.springer.com/article/10.1038/s41598-019-57325-7
http://link.springer.com/article/10.1038/s41598-019-57325-7
Autor:
Sanjay Saini, Ruhani Doda Khera, Fatemeh Homayounieh, Andrew N. Primak, Mannudeep K. Kalra, Martin Sedlmair, Bernhard Schmidt, Felix Lades
Publikováno v:
Journal of Computer Assisted Tomography. 44:223-229
Objectives This study aimed to assess if dual-energy computed tomography (DECT) quantitative analysis and radiomics can differentiate normal liver, hepatic steatosis, and cirrhosis. Materials and methods Our retrospective study included 75 adult pati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::337a2c90c7e234efa5e272a21e07e9a3
https://doi.org/10.1097/rct.0000000000000989
https://doi.org/10.1097/rct.0000000000000989
Autor:
Ramandeep Singh, Sanjay Sharma, Shadi Ebrahimian, Mannudeep K. Kalra, Fatemeh Homayounieh, Felix Lades, Arjunlokesh Netaji, Kumble Seetharama Madhusudhan, Sanjay Saini, Andrew N. Primak
Publikováno v:
Academic radiology. 29(5)
Rationale and Objectives To compare dual energy CT (DECT) quantitative metrics and radiomics for differentiating benign and malignant pancreatic lesions on contrast enhanced abdomen CT. Materials and Methods Our study included 103 patients who underw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4da0c6abeeaf08781485bd3002fee90f
https://pubmed.ncbi.nlm.nih.gov/34412944
https://pubmed.ncbi.nlm.nih.gov/34412944
Autor:
Fatemeh Homayounieh, Subba R. Digumarthy, Shadi Ebrahimian, Sandeep Hedgire, Mannudeep K. Kalra, Felix Lades, Andrew N. Primak
Publikováno v:
The International Journal of Cardiovascular Imaging
To assess if radiomics can differentiate left atrial appendage (LAA) contrast-mixing artifacts and thrombi on early-phase CT angiography without the need for late-phase images. Our study included 111 patients who underwent early- and late-phase, cont
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c525ea6031b9dcd7ed800c46734d413
https://pubmed.ncbi.nlm.nih.gov/33544242
https://pubmed.ncbi.nlm.nih.gov/33544242
Autor:
Michael Wels, Volker Heinemann, Dominik Nörenberg, Julian Walter Holch, Martine Remy-Jardin, Oliver Taubmann, Michael Sühling, Alexander Mühlberg, Stefan Maurus, Felix Lades, Rainer Kärgel, Alexander Katzmann, Jean-Baptiste Faivre, Thomas Huber
Publikováno v:
Scientific Reports
Scientific Reports, Vol 10, Iss 1, Pp 1-1 (2020)
Scientific Reports, Vol 10, Iss 1, Pp 1-1 (2020)
The goal of radiomics is to convert medical images into a minable data space by extraction of quantitative imaging features for clinically relevant analyses, e.g. survival time prediction of a patient. One problem of radiomics from computed tomograph
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0480bf0504aba07ff72fadb6e2a09873
https://doi.org/10.1038/s41598-020-68534-w
https://doi.org/10.1038/s41598-020-68534-w
Publikováno v:
Medical Imaging: Computer-Aided Diagnosis
In this paper we present an integrated software solution∗ targeting clinical researchers for discovering relevant radiomic biomarkers covering the entire value chain of clinical radiomics research. Its intention is to make this kind of research pos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca6afad46a54cc67dfe9a1c8454e6e62
https://doi.org/10.1117/12.2511856
https://doi.org/10.1117/12.2511856
