Zobrazeno 1 - 10
of 111
pro vyhledávání: '"Lafata, Kyle J"'
Autor:
Dahal, Lavsen, Ghojoghnejad, Mobina, Ghosh, Dhrubajyoti, Bhandari, Yubraj, Kim, David, Ho, Fong Chi, Tushar, Fakrul Islam, Luoa, Sheng, Lafata, Kyle J., Abadi, Ehsan, Samei, Ehsan, Lo, Joseph Y., Segars, W. Paul
Virtual Imaging Trials (VIT) offer a cost-effective and scalable approach for evaluating medical imaging technologies. Computational phantoms, which mimic real patient anatomy and physiology, play a central role in VITs. However, the current librarie
Externí odkaz:
http://arxiv.org/abs/2405.11133
Autor:
Tushar, Fakrul Islam, Wang, Avivah, Dahal, Lavsen, Harowicz, Michael R., Lafata, Kyle J., Tailor, Tina D., Lo, Joseph Y.
Lung cancer's high mortality rate can be mitigated by early detection, increasingly reliant on AI for diagnostic imaging. However, AI model performance depends on training and validation datasets. This study develops and validates AI models for both
Externí odkaz:
http://arxiv.org/abs/2405.04605
Autor:
Tushar, Fakrul Islam, Vancoillie, Liesbeth, McCabe, Cindy, Kavuri, Amareswararao, Dahal, Lavsen, Harrawood, Brian, Fryling, Milo, Zarei, Mojtaba, Sotoudeh-Paima, Saman, Ho, Fong Chi, Ghosh, Dhrubajyoti, Harowicz, Michael R., Tailor, Tina D., Luo, Sheng, Segars, W. Paul, Abadi, Ehsan, Lafata, Kyle J., Lo, Joseph Y., Samei, Ehsan
Objectives: To demonstrate that a virtual imaging trial platform can accurately emulate a major clinical trial, specifically the National Lung Screening Trial (NLST) that compared computed tomography (CT) and chest radiography (CXR) imaging for lung
Externí odkaz:
http://arxiv.org/abs/2404.11221
Autor:
Mouheb, Kaouther, Nejad, Mobina Ghojogh, Dahal, Lavsen, Samei, Ehsan, Lafata, Kyle J., Segars, W. Paul, Lo, Joseph Y.
Accurate 3D modeling of human organs plays a crucial role in building computational phantoms for virtual imaging trials. However, generating anatomically plausible reconstructions of organ surfaces from computed tomography scans remains challenging f
Externí odkaz:
http://arxiv.org/abs/2309.08289
Autor:
Wang, Yuqi, Macdonald, Jacob A., Morgan, Katelyn R., Hom, Danielle, Cubberley, Sarah, Sollace, Kassi, Casasanto, Nicole, Zaki, Islam H., Lafata, Kyle J., Bashir, Mustafa R.
Spleen volumetry is primarily associated with patients suffering from chronic liver disease and portal hypertension, as they often have spleens with abnormal shapes and sizes. However, manually segmenting the spleen to obtain its volume is a time-con
Externí odkaz:
http://arxiv.org/abs/2305.05732
Autor:
Zhao, Jingtong, Vaios, Eugene, Wang, Yuqi, Yang, Zhenyu, Cui, Yunfeng, Reitman, Zachary J., Lafata, Kyle J., Fecci, Peter, Kirkpatrick, John, Fang Yin, Fang, Floyd, Scott, Wang, Chunhao
Publikováno v:
In International Journal of Radiation Oncology, Biology, Physics 1 October 2024 120(2):603-613
To develop a deep-learning model that integrates radiomics analysis for enhanced performance of COVID-19 and Non-COVID-19 pneumonia detection using chest X-ray image, two deep-learning models were trained based on a pre-trained VGG-16 architecture: i
Externí odkaz:
http://arxiv.org/abs/2107.08667
Autor:
Lafata, Kyle J., Read, Charlotte, Tong, Betty C., Akinyemiju, Tomi, Wang, Chunhao, Cerullo, Marcelo, Tailor, Tina D.
Publikováno v:
In Journal of the American College of Radiology May 2024 21(5):767-777
Autor:
Yang, Zhenyu, Lafata, Kyle J, Chen, Xinru, Bowsher, James, Chang, Yushi, Wang, Chunhao, Yin, Fang-Fang
Purpose: To develop a radiomics filtering technique for characterizing spatial-encoded regional pulmonary ventilation information on lung CT. Methods: The lung volume was segmented on 46 CT images, and a 3D sliding window kernel was implemented acros
Externí odkaz:
http://arxiv.org/abs/2105.11171
Autor:
Glass, Carolyn, Lafata, Kyle J., Jeck, William, Horstmeyer, Roarke, Cooke, Colin, Everitt, Jeffrey, Glass, Matthew, Dov, David, Seidman, Michael A.
Publikováno v:
In Canadian Journal of Cardiology February 2022 38(2):234-245