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pro vyhledávání: '"Myers, Kyle"'
Brightness mode (B-mode) ultrasound is a common imaging modality in the clinical assessment of several cardiovascular diseases. The utility of ultrasound-based functional indices such as the ejection fraction (EF) and stroke volume (SV) is widely des
Externí odkaz:
http://arxiv.org/abs/2409.04577
Lung injuries, such as ventilator-induced lung injury and radiation-induced lung injury, can lead to heterogeneous alterations in the biomechanical behavior of the lungs. While imaging methods, e.g., X-ray and static computed tomography (CT), can poi
Externí odkaz:
http://arxiv.org/abs/2407.03457
Report on the AAPM Grand Challenge on deep generative modeling for learning medical image statistics
Autor:
Deshpande, Rucha, Kelkar, Varun A., Gotsis, Dimitrios, Kc, Prabhat, Zeng, Rongping, Myers, Kyle J., Brooks, Frank J., Anastasio, Mark A.
The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. The goal of this challenge was to promote the development of deep generative models (DGMs) for medica
Externí odkaz:
http://arxiv.org/abs/2405.01822
Autor:
Myers, Kyle, Tham, Wei Yang
The design of research grants has been hypothesized to be a useful tool for influencing researchers and their science. We test this by conducting two thought experiments in a nationally representative survey of academic researchers. First, we offer p
Externí odkaz:
http://arxiv.org/abs/2312.06479
Autor:
Myers, Kyle R., Tham, Wei Yang, Thursby, Jerry, Thursby, Marie, Cohodes, Nina, Lakhani, Karim, Mural, Rachel, Xu, Yilun
We introduce a new survey of professors at roughly 150 of the most research-intensive institutions of higher education in the US. We document seven new features of how research-active professors are compensated, how they spend their time, and how the
Externí odkaz:
http://arxiv.org/abs/2312.01442
Autor:
Whitney, Heather M., Baughan, Natalie, Myers, Kyle J., Drukker, Karen, Gichoya, Judy, Bower, Brad, Chen, Weijie, Gruszauskas, Nicholas, Kalpathy-Cramer, Jayashree, Koyejo, Sanmi, Sá, Rui C., Sahiner, Berkman, Zhang, Zi, Giger, Maryellen L.
Purpose: The Medical Imaging and Data Resource Center (MIDRC) open data commons was launched to accelerate the development of artificial intelligence (AI) algorithms to help address the COVID-19 pandemic. The purpose of this study was to quantify lon
Externí odkaz:
http://arxiv.org/abs/2303.10501
Autor:
Lyu, Qing, Tan, Josh, Zapadka, Michael E., Ponnatapura, Janardhana, Niu, Chuang, Myers, Kyle J., Wang, Ge, Whitlow, Christopher T.
The large language model called ChatGPT has drawn extensively attention because of its human-like expression and reasoning abilities. In this study, we investigate the feasibility of using ChatGPT in experiments on using ChatGPT to translate radiolog
Externí odkaz:
http://arxiv.org/abs/2303.09038
Autor:
Myers, Kyle R.
When funding public goods, resources are often allocated via mechanisms that resemble contests, especially in the case of research grants. A common critique of these contests is that they induce ``too much'' effort from participants. This need not be
Externí odkaz:
http://arxiv.org/abs/2207.02379
Assessing the ability of generative adversarial networks to learn canonical medical image statistics
Autor:
Kelkar, Varun A., Gotsis, Dimitrios S., Brooks, Frank J., KC, Prabhat, Myers, Kyle J., Zeng, Rongping, Anastasio, Mark A.
In recent years, generative adversarial networks (GANs) have gained tremendous popularity for potential applications in medical imaging, such as medical image synthesis, restoration, reconstruction, translation, as well as objective image quality ass
Externí odkaz:
http://arxiv.org/abs/2204.12007
Autor:
Kelkar, Varun A., Gotsis, Dimitrios S., Brooks, Frank J., Myers, Kyle J., KC, Prabhat, Zeng, Rongping, Anastasio, Mark A.
Modern generative models, such as generative adversarial networks (GANs), hold tremendous promise for several areas of medical imaging, such as unconditional medical image synthesis, image restoration, reconstruction and translation, and optimization
Externí odkaz:
http://arxiv.org/abs/2204.03547