Performance of a deep learning tool to detect missed aortic dilatation in a large chest CT cohort

Autor: Maurice Pradella, Rita Achermann, Jonathan I. Sperl, Rainer Kärgel, Saikiran Rapaka, Joshy Cyriac, Shan Yang, Gregor Sommer, Bram Stieltjes, Jens Bremerich, Philipp Brantner, Alexander W. Sauter

Publikováno v: Frontiers in Cardiovascular Medicine, Vol 9 (2022)

PurposeThoracic aortic (TA) dilatation (TAD) is a risk factor for acute aortic syndrome and must therefore be reported in every CT report. However, the complex anatomy of the thoracic aorta impedes TAD detection. We investigated the performance of a

Externí odkaz: https://doaj.org/article/f5c08b69ce83495cb0fe2c96a6c1fd0a

Reduction in Radiologist Interpretation Time of Serial CT and MR Imaging Findings with Deep Learning Identification of Relevant Priors, Series and Finding Locations

Autor: Thomas Weikert, Harold I. Litt, William H. Moore, Mohammed Abed, Lea Azour, Abass M. Noor, Liene Friebe, Nathaniel Linna, Halid Ziya Yerebakan, Yoshihisa Shinagawa, Gerardo Hermosillo, Simon Allen-Raffl, Mahesh Ranganath, Alexander W. Sauter

Publikováno v: Academic Radiology.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6ff3afc10c42a2f4160e89da267fe7cb
https://doi.org/10.1016/j.acra.2023.03.041

Automated Detection of Pancreatic Cystic Lesions on CT Using Deep Learning

Autor: Lorraine Abel, Jakob Wasserthal, Thomas Weikert, Alexander W. Sauter, Ivan Nesic, Marko Obradovic, Shan Yang, Sebastian Manneck, Carl Glessgen, Johanna M. Ospel, Bram Stieltjes, Daniel T. Boll, Björn Friebe

Publikováno v: Diagnostics, Vol 11, Iss 5, p 901 (2021)

Pancreatic cystic lesions (PCL) are a frequent and underreported incidental finding on CT scans and can transform into neoplasms with devastating consequences. We developed and evaluated an algorithm based on a two-step nnU-Net architecture for autom

Externí odkaz: https://doaj.org/article/adcd95dab082416face4eea33cc27e47

Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium

Autor: Tugba Akinci D'Antonoli, Shan Yang, Gregor Sommer, Constantin Anastasopoulos, Marco Reisert, Sven Knecht, Rita Achermann, Maurice Pradella, Philip Haaf, Elias Kellner, Ahmed Abdulkadir, Bram Stieltjes, Jens Bremerich, Joshy Cyriac, Alexander W. Sauter

Publikováno v: Journal of Cardiovascular Magnetic Resonance, Vol 23, Iss 1, Pp 1-10 (2021)
Journal of Cardiovascular Magnetic Resonance
Anastasopoulos, Constantin; Yang, Shan; Pradella, Maurice; Akinci D’Antonoli, Tugba; Knecht, Sven; Cyriac, Joshy; Reisert, Marco; Kellner, Elias; Achermann, Rita; Haaf, Philip; Stieltjes, Bram; Sauter, Alexander W.; Bremerich, Jens; Sommer, Gregor; Abdulkadir, Ahmed (2021). Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium. Journal of cardiovascular magnetic resonance, 23(1), p. 133. BioMed Central 10.1186/s12968-021-00791-8

Background Artificial intelligence can assist in cardiac image interpretation. Here, we achieved a substantial reduction in time required to read a cardiovascular magnetic resonance (CMR) study to estimate left atrial volume without compromising accu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::756f9983d0f9444683a02cf244ccbbcc
https://doaj.org/article/2c7dad674455468f9cb132fffb8fde99

Acute Pulmonary Embolism in COVID-19: A Potential Connection between Venous Congestion and Thrombus Distribution

Autor: Franck, Nevesny, David C, Rotzinger, Alexander W, Sauter, Laura I, Loebelenz, Lena, Schmuelling, Hatem, Alkadhi, Lukas, Ebner, Andreas, Christe, Alexandra, Platon, Pierre-Alexandre, Poletti, Salah D, Qanadli

Publikováno v: Biomedicines, vol. 10, no. 6, pp. 1300

Vascular abnormalities, including venous congestion (VC) and pulmonary embolism (PE), have been recognized as frequent COVID-19 imaging patterns and proposed as severity markers. However, the underlying pathophysiological mechanisms remain unclear. I

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::e9649f0e5d873ad0b36a905ff3822859
https://serval.unil.ch/notice/serval:BIB_8CA280011B0B