Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Tanveer Gupte"'
Autor:
Pranav Ajmera, Prashant Onkar, Sanjay Desai, Richa Pant, Jitesh Seth, Tanveer Gupte, Viraj Kulkarni, Amit Kharat, Nandini Passi, Sanjay Khaladkar, V. M. Kulkarni
Publikováno v:
Diagnostics, Vol 13, Iss 3, p 557 (2023)
Purpose: Manual interpretation of chest radiographs is a challenging task and is prone to errors. An automated system capable of categorizing chest radiographs based on the pathologies identified could aid in the timely and efficient diagnosis of che
Externí odkaz:
https://doaj.org/article/e0f98aadd09d40768a7040ab0e085033
Autor:
Pranav Ajmera, Amit Kharat, Sanjay Khaladkar, Tanveer Gupte, Richa Pant, Viraj Kulkarni, Vinay Duddalwar, Deepak Patkar, Mona Bhatia, Purnachandra Lamghare
IntroductionUsing artificial intelligence in imaging practice helps ensure study list reprioritization, prompt attention to urgent studies, and reduces the reporting turn-around time.PurposeWe tested a deep learning-based artificial intelligence mode
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5e081b3455fafbfa7d436c09a4a17a8
https://doi.org/10.1101/2022.06.02.22275895
https://doi.org/10.1101/2022.06.02.22275895
Autor:
Tanveer Gupte, Richa Pant, Kapil Zirpe, Dinesh Shende, Avinash Nanivadekar, Rohit Lokwani, Rajan Patel, Amit Kharat, Ashutosh Dwivedi, Viraj Kulkarni
BackgroundEarly prediction of disease severity in COVID-19 patients is essential. Chest X-ray (CXR) is a faster, widely available, and less expensive imaging modality that may be useful in predicting mortality in COVID-19 patients. Artificial Intelli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a9fb8ee3b382d07563d006bbe18e380
https://doi.org/10.1101/2021.09.22.21263956
https://doi.org/10.1101/2021.09.22.21263956
Autor:
Pranav Ajmera, Amit Kharat, Tanveer Gupte, Richa Pant, Viraj Kulkarni, Vinay Duddalwar, Purnachandra Lamghare
Publikováno v:
Acta Radiologica Open. 11:205846012211073
Background Cardiothoracic ratio (CTR) is the ratio of the diameter of the heart to the diameter of the thorax. An abnormal CTR (>0.55) is often an indicator of an underlying pathological condition. The accurate prediction of an abnormal CTR chest X-r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f0470ada51246c87dd93163e41900d1
https://doi.org/10.1177/20584601221107345
https://doi.org/10.1177/20584601221107345
We propose an automated method based on deep learning to compute the cardiothoracic ratio and detect the presence of cardiomegaly from chest radiographs. We develop two separate models to demarcate the heart and chest regions in an X-ray image using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d3514a8b8f7627453d3623800d193a35