Zobrazeno 1 - 10
of 46
pro vyhledávání: '"P. Díaz Pinto"'
Autor:
Liu, Yihao, Zhang, Jiaming, Diaz-Pinto, Andres, Li, Haowei, Martin-Gomez, Alejandro, Kheradmand, Amir, Armand, Mehran
The Segment Anything Model (SAM) has drawn significant attention from researchers who work on medical image segmentation because of its generalizability. However, researchers have found that SAM may have limited performance on medical images compared
Externí odkaz:
http://arxiv.org/abs/2403.18114
Autor:
Diaz-Pinto, Andres, Mehta, Pritesh, Alle, Sachidanand, Asad, Muhammad, Brown, Richard, Nath, Vishwesh, Ihsani, Alvin, Antonelli, Michela, Palkovics, Daniel, Pinter, Csaba, Alkalay, Ron, Pieper, Steve, Roth, Holger R., Xu, Daguang, Dogra, Prerna, Vercauteren, Tom, Feng, Andrew, Quraini, Abood, Ourselin, Sebastien, Cardoso, M. Jorge
Automatic segmentation of medical images is a key step for diagnostic and interventional tasks. However, achieving this requires large amounts of annotated volumes, which can be tedious and time-consuming task for expert annotators. In this paper, we
Externí odkaz:
http://arxiv.org/abs/2305.10655
Autor:
Cardoso, M. Jorge, Li, Wenqi, Brown, Richard, Ma, Nic, Kerfoot, Eric, Wang, Yiheng, Murrey, Benjamin, Myronenko, Andriy, Zhao, Can, Yang, Dong, Nath, Vishwesh, He, Yufan, Xu, Ziyue, Hatamizadeh, Ali, Zhu, Wentao, Liu, Yun, Zheng, Mingxin, Tang, Yucheng, Yang, Isaac, Zephyr, Michael, Hashemian, Behrooz, Alle, Sachidanand, Darestani, Mohammad Zalbagi, Budd, Charlie, Modat, Marc, Vercauteren, Tom, Wang, Guotai, Li, Yiwen, Hu, Yipeng, Fu, Yunguan, Gorman, Benjamin, Johnson, Hans, Genereaux, Brad, Erdal, Barbaros S., Gupta, Vikash, Diaz-Pinto, Andres, Dourson, Andre, Maier-Hein, Lena, Jaeger, Paul F., Baumgartner, Michael, Kalpathy-Cramer, Jayashree, Flores, Mona, Kirby, Justin, Cooper, Lee A. D., Roth, Holger R., Xu, Daguang, Bericat, David, Floca, Ralf, Zhou, S. Kevin, Shuaib, Haris, Farahani, Keyvan, Maier-Hein, Klaus H., Aylward, Stephen, Dogra, Prerna, Ourselin, Sebastien, Feng, Andrew
Artificial Intelligence (AI) is having a tremendous impact across most areas of science. Applications of AI in healthcare have the potential to improve our ability to detect, diagnose, prognose, and intervene on human disease. For AI models to be use
Externí odkaz:
http://arxiv.org/abs/2211.02701
Autor:
Inés, Adrián, Díaz-Pinto, Andrés, Domínguez, César, Heras, Jónathan, Mata, Eloy, Pascual, Vico
The development of mobile and on the edge applications that embed deep convolutional neural models has the potential to revolutionise biomedicine. However, most deep learning models require computational resources that are not available in smartphone
Externí odkaz:
http://arxiv.org/abs/2205.09678
Autor:
Diaz-Pinto, Andres, Alle, Sachidanand, Nath, Vishwesh, Tang, Yucheng, Ihsani, Alvin, Asad, Muhammad, Pérez-García, Fernando, Mehta, Pritesh, Li, Wenqi, Flores, Mona, Roth, Holger R., Vercauteren, Tom, Xu, Daguang, Dogra, Prerna, Ourselin, Sebastien, Feng, Andrew, Cardoso, M. Jorge
The lack of annotated datasets is a major bottleneck for training new task-specific supervised machine learning models, considering that manual annotation is extremely expensive and time-consuming. To address this problem, we present MONAI Label, a f
Externí odkaz:
http://arxiv.org/abs/2203.12362
Autor:
Orlando, José Ignacio, Fu, Huazhu, Breda, João Barbossa, van Keer, Karel, Bathula, Deepti R., Diaz-Pinto, Andrés, Fang, Ruogu, Heng, Pheng-Ann, Kim, Jeyoung, Lee, JoonHo, Lee, Joonseok, Li, Xiaoxiao, Liu, Peng, Lu, Shuai, Murugesan, Balamurali, Naranjo, Valery, Phaye, Sai Samarth R., Shankaranarayana, Sharath M., Sikka, Apoorva, Son, Jaemin, Hengel, Anton van den, Wang, Shujun, Wu, Junyan, Wu, Zifeng, Xu, Guanghui, Xu, Yongli, Yin, Pengshuai, Li, Fei, Zhang, Xiulan, Xu, Yanwu, Bogunović, Hrvoje
Glaucoma is one of the leading causes of irreversible but preventable blindness in working age populations. Color fundus photography (CFP) is the most cost-effective imaging modality to screen for retinal disorders. However, its application to glauco
Externí odkaz:
http://arxiv.org/abs/1910.03667
Akademický článek
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Akademický článek
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Autor:
Malucha Subiabre, José Manuel Izquierdo, Luis Merino Montero, Juan Pablo González, Alejandro Vera, Daniela Banderas G., Daniel Party, Christian Spencer, Valentina Salinas Welsh, Daniela Maltrain, Daniela Sepúlveda, Macarena Robledo Thompson, Ana María Díaz Pinto, Tamara Bulicic Auspont
Publikováno v:
Resonancias, Vol 26, Iss 50, Pp 217-230 (2022)
Externí odkaz:
https://doaj.org/article/a9356001809a4e40a518dc7dab01b8d1
Autor:
Vesal, Sulaiman, Diaz-Pinto, Andres, Ravikumar, Nishant, Ellmann, Stephan, Davari, Amirabbas, Maier, Andreas
Magnetic resonance imaging (MRI) is an effective imaging modality for identifying and localizing breast lesions in women. Accurate and precise lesion segmentation using a computer-aided-diagnosis (CAD) system, is a crucial step in evaluating tumor vo
Externí odkaz:
http://arxiv.org/abs/1712.05200