Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Tomar, Nikhil"'
Autor:
Jha, Debesh, Tomar, Nikhil Kumar, Sharma, Vanshali, Trinh, Quoc-Huy, Biswas, Koushik, Pan, Hongyi, Jha, Ritika K., Durak, Gorkem, Hann, Alexander, Varkey, Jonas, Dao, Hang Viet, Van Dao, Long, Nguyen, Binh Phuc, Pham, Khanh Cong, Tran, Quang Trung, Papachrysos, Nikolaos, Rieders, Brandon, Schmidt, Peter Thelin, Geissler, Enrik, Berzin, Tyler, Halvorsen, Pål, Riegler, Michael A., de Lange, Thomas, Bagci, Ulas
Colonoscopy is the primary method for examination, detection, and removal of polyps. Regular screening helps detect and prevent colorectal cancer at an early curable stage. However, challenges such as variation among the endoscopists' skills, bowel q
Externí odkaz:
http://arxiv.org/abs/2409.00045
Autor:
Jha, Debesh, Tomar, Nikhil Kumar, Biswas, Koushik, Durak, Gorkem, Antalek, Matthew, Zhang, Zheyuan, Wang, Bin, Rahman, Md Mostafijur, Pan, Hongyi, Medetalibeyoglu, Alpay, Velichko, Yury, Ladner, Daniela, Borhani, Amir, Bagci, Ulas
Accurate segmentation of organs from abdominal CT scans is essential for clinical applications such as diagnosis, treatment planning, and patient monitoring. To handle challenges of heterogeneity in organ shapes, sizes, and complex anatomical relatio
Externí odkaz:
http://arxiv.org/abs/2405.06166
Autor:
Das, Abhijit, Jha, Debesh, Sanjotra, Jasmer, Susladkar, Onkar, Sarkar, Suramyaa, Rauniyar, Ashish, Tomar, Nikhil, Sharma, Vanshali, Bagci, Ulas
Foundational models (FMs) have tremendous potential to revolutionize medical imaging. However, their deployment in real-world clinical settings demands extensive ethical considerations. This paper aims to highlight the ethical concerns related to FMs
Externí odkaz:
http://arxiv.org/abs/2406.11868
Autor:
Jha, Debesh, Tomar, Nikhil Kumar, Biswas, Koushik, Durak, Gorkem, Medetalibeyoglu, Alpay, Antalek, Matthew, Velichko, Yury, Ladner, Daniela, Borhani, Amir, Bagci, Ulas
Accurate liver segmentation from CT scans is essential for effective diagnosis and treatment planning. Computer-aided diagnosis systems promise to improve the precision of liver disease diagnosis, disease progression, and treatment planning. In respo
Externí odkaz:
http://arxiv.org/abs/2401.09630
Autor:
Biswas, Koushik, Jha, Debesh, Tomar, Nikhil Kumar, Durak, Gorkem, Medetalibeyoglu, Alpay, Antalek, Matthew, Velichko, Yury, Ladner, Daniela, Bohrani, Amir, Bagci, Ulas
In this study, we propose a new activation function, called Adaptive Smooth Activation Unit (ASAU), tailored for optimized gradient propagation, thereby enhancing the proficiency of convolutional networks in medical image analysis. We apply this new
Externí odkaz:
http://arxiv.org/abs/2312.11480
Existing polyp segmentation models from colonoscopy images often fail to provide reliable segmentation results on datasets from different centers, limiting their applicability. Our objective in this study is to create a robust and well-generalized se
Externí odkaz:
http://arxiv.org/abs/2308.03709
Autor:
Jha, Debesh, Sharma, Vanshali, Banik, Debapriya, Bhattacharya, Debayan, Roy, Kaushiki, Hicks, Steven A., Tomar, Nikhil Kumar, Thambawita, Vajira, Krenzer, Adrian, Ji, Ge-Peng, Poudel, Sahadev, Batchkala, George, Alam, Saruar, Ahmed, Awadelrahman M. A., Trinh, Quoc-Huy, Khan, Zeshan, Nguyen, Tien-Phat, Shrestha, Shruti, Nathan, Sabari, Gwak, Jeonghwan, Jha, Ritika K., Zhang, Zheyuan, Schlaefer, Alexander, Bhattacharjee, Debotosh, Bhuyan, M. K., Das, Pradip K., Fan, Deng-Ping, Parsa, Sravanthi, Ali, Sharib, Riegler, Michael A., Halvorsen, Pål, De Lange, Thomas, Bagci, Ulas
Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps during the live examination can be challenging due to various factors such
Externí odkaz:
http://arxiv.org/abs/2307.16262
Autor:
Jha, Debesh, Sharma, Vanshali, Dasu, Neethi, Tomar, Nikhil Kumar, Hicks, Steven, Bhuyan, M. K., Das, Pradip K., Riegler, Michael A., Halvorsen, Pål, Bagci, Ulas, de Lange, Thomas
Integrating real-time artificial intelligence (AI) systems in clinical practices faces challenges such as scalability and acceptance. These challenges include data availability, biased outcomes, data quality, lack of transparency, and underperformanc
Externí odkaz:
http://arxiv.org/abs/2307.08140
Colorectal cancer is among the most common cause of cancer worldwide. Removal of precancerous polyps through early detection is essential to prevent them from progressing to colon cancer. We develop an advanced deep learning-based architecture, Trans
Externí odkaz:
http://arxiv.org/abs/2306.02176
Autor:
Jha, Debesh, Rauniyar, Ashish, Srivastava, Abhiskek, Hagos, Desta Haileselassie, Tomar, Nikhil Kumar, Sharma, Vanshali, Keles, Elif, Zhang, Zheyuan, Demir, Ugur, Topcu, Ahmet, Yazidi, Anis, Håakegård, Jan Erik, Bagci, Ulas
Artificial intelligence (AI) methods hold immense potential to revolutionize numerous medical care by enhancing the experience of medical experts and patients. AI-based computer-assisted diagnosis and treatment tools can democratize healthcare by mat
Externí odkaz:
http://arxiv.org/abs/2304.11530