Dr. Gabriella Worwa Profile

Dr. Gabriella Worwa

at National Institutes of Health

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Publications (6)

Proceedings Article | 2 April 2024 Poster + Paper

Active learning applied to selection of diverse training data using radiomic features for optimal lung lesion segmentation in nonhuman primates

Mark Rustad, Winston Chu, Syed Reza, Philip Sayre, Ian Crozier, Gabriella Worwa, Jens Kuhn, Claudia Calcagno, Marcelo Castro, Jeffrey Solomon

Proceedings Volume 12930, 129301X (2024) https://doi.org/10.1117/12.3006808

KEYWORDS: Data modeling, Image segmentation, Computed tomography, Radiomics, Performance modeling, Lung, Active learning, Animals, Pulmonary disorders

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Proceedings Article | 2 April 2024 Presentation + Paper

Lung lesion segmentation of CT scans after SARS-CoV-2 infection: combining nonhuman primate with human data for interspecies transfer learning

Linh Shinguyen, Winston Chu, Mark Rustad, Ashkan Malayeri, Maryam Homayounieh, Shiva Singh, Claudia Calcagno, Philip Sayre, Ian Crozier, Gabriella Worwa, Jens Kuhn, Bradford Wood, Marcelo Castro, Jeffrey Solomon

Proceedings Volume 12930, 1293010 (2024) https://doi.org/10.1117/12.3006206

KEYWORDS: Computed tomography, Data modeling, Lung, Education and training, Viruses, Pulmonary disorders, Deep learning, Medical imaging, Image segmentation, Image enhancement

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SPIE Journal Paper | 8 December 2023

Repeatability of computed tomography liver radiomic features in a nonhuman primate model of diet-induced steatosis

Hui Wang, Jeffrey Solomon, Syed M. Reza, Hee-Jeong Yang, Winston T. Chu, Ian Crozier, Philip Sayre, Byeong Lee, Venkatesh Mani, Thomas Friedrich, David O’Connor, Gabriella Worwa, Jens Kuhn, Claudia Calcagno, Marcelo Castro

JMI, Vol. 10, Issue 06, 066004, (December 2023) https://doi.org/10.1117/12.10.1117/1.JMI.10.6.066004

KEYWORDS: Radiomics, Liver, Computed tomography, Cooccurrence matrices, Attenuation, Feature extraction, Diseases and disorders, Animals, Medical image reconstruction, Spleen

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Proceedings Article | 10 April 2023 Poster + Paper

Determination of reproducible radiomic features for diagnosis of fatty liver disease in a crab-eating macaque model

Hui Wang, Jeffrey Solomon, Syed Reza, Hee-Jeong Yang, Ian Crozier, Philip Sayre, Winston Chu, Byeong-Yeul Lee, Venkatesh Mani, Thomas Friedrich, David O'Connor, Willem J. Mulder, Gabriella Worwa, Jens Kuhn, Claudia Calcagno, Marcelo Castro

Proceedings Volume 12468, 1246819 (2023) https://doi.org/10.1117/12.2647632

KEYWORDS: Reproducibility, Radiomics, Computed tomography, Liver, Diseases and disorders, Animals, Feature extraction, Attenuation, Spleen, Medical image reconstruction

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SPIE Journal Paper | 8 December 2022 Open Access

Toward the determination of sensitive and reliable whole-lung computed tomography features for robust standard radiomics and delta-radiomics analysis in a nonhuman primate model of coronavirus disease 2019

Marcelo Castro, Syed M. Reza, Winston Chu, Dara Bradley, Ji Hyun Lee, Ian Crozier, Philip Sayre, Byeong Lee, Venkatesh Mani, Thomas Friedrich, David O’Connor, Courtney Finch, Gabriella Worwa, Irwin M. Feuerstein, Jens Kuhn, Jeffrey Solomon

JMI, Vol. 9, Issue 06, 066003, (December 2022) https://doi.org/10.1117/12.10.1117/1.JMI.9.6.066003

KEYWORDS: Animals, Radiomics, Cooccurrence matrices, Computed tomography, Reliability, Feature extraction, COVID 19, Image segmentation, Lung, Animal model studies

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Proceedings Article | 4 April 2022 Poster + Paper

Determination of reliable whole-lung CT features for robust standard radiomics and delta-radiomics analysis in a crab-eating macaque model of COVID-19: stability and sensitivity analysis

Marcelo Castro, Syed Reza, Winston Chu, Dara Bradley, Ji Hyun Lee, Ian Crozier, Philip Sayre, Byeong Lee, Venkatesh Mani, Thomas Friedrich, David O'Connor, Courtney Finch, Gabriella Worwa, Irwin Feuerstein, Jens Kuhn, Jeffrey Solomon

Proceedings Volume 12036, 1203621 (2022) https://doi.org/10.1117/12.2607154

KEYWORDS: Reliability, Computed tomography, Feature extraction, Image segmentation, Animal model studies, Lung, Signal attenuation, Scanners, Volume segmentation, Artificial intelligence

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