Ms. Veda Murthy Profile

Veda Murthy

at Univ of Southern California

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Publications (4)

Proceedings Article | 4 April 2022 Presentation

Dual-tier segmentation approach for hard exudates in fundus images with U-net convolutional neural network

Soumika Guduru, Emma Munch, Veda Murthy, Brent Liu

Proceedings Volume PC12037, PC120370A (2022) https://doi.org/10.1117/12.2612925

KEYWORDS: Image segmentation, Convolutional neural networks, Optical discs, Surveillance, Integration, Blood vessels

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Proceedings Article | 15 March 2019 Presentation + Paper

Head and neck cancer radiation therapy decision support

Trent Benedick, Veda Murthy, Rhea Koparde, Maying Shi, Sabrina Lieu, Siliang Zhang, Benjamin Yao, Anh Le, Brent Liu

Proceedings Volume 10954, 109540Y (2019) https://doi.org/10.1117/12.2513075

KEYWORDS: Cancer, Radiotherapy, Decision support systems, Head, Neck, Feature extraction, Tumors, Databases, Oncology, Information science

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Currently the methods used to develop radiation therapy treatment plans for head and neck cancers rely on clinician experience and a small set of universal guidelines which result in inconsistent and variable methods. Data driven support can provide assistance to clinicians by reducing inconsistency associated with treatment planning and provide empirical estimates to minimize the radiation to healthy organs near the tumor. We created a database of DICOM RT objects which stores historical cases and when a new DICOM object is uploaded it will return a set of similar treatment plans to assist the clinician in creating the treatment plan for the current patient. The database works first by extracting features from DICOM RT object to quantitatively compare and evaluate the similarity of cases enabling the system to mine for cases with defined similarity. The feature extraction methods are based on the spatial relationships between the tumors and organs at risk which allows the generation the overlap volume histogram and spatial target similarity which demonstrate the volumetric and locational similarity between the organ at risk and the tumor. It is useful to find cases with similar tumor anatomy because this similarity translates to similarity in radiation dosage. The developed system was applied to three different RT sites, University of California Los Angeles, Technical University at Munich and State University of New York Buffalo; Roswell Park, with a total of 247 cases to evaluate the system for both inter- and intra- institutional best practices and results. Future roadmap will be discussed for correlating outcomes results to the decision support system which will enhance the overall performance and utilization of the decision support system in the RT workflow. In the future, because this database returns similar historical cases to a current one this could be a worthwhile decision support tool for clinicians as they create new radiation therapy treatment plans.

Proceedings Article | 15 March 2019 Presentation + Paper

Fundus Analysis Software Tool (FAST): development of software integrating CAD with the EHR for the longitudinal study of fundus images

Veda Murthy, Manjula Shankar, Justin Lin, Sabrina Lieu, Mayur Patel, Heaven Post, Hemanth Murthy, Brent Liu

Proceedings Volume 10954, 1095406 (2019) https://doi.org/10.1117/12.2512068

KEYWORDS: Image segmentation, Computer aided design, Algorithm development, Image processing algorithms and systems, Software development, Computer aided diagnosis and therapy, Image processing, Java

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Proceedings Article | 6 March 2018 Presentation + Paper

The application of deep learning for diabetic retinopathy prescreening in research eye-PACS

Siliang Zhang, Huiqun Wu, Veda Murthy, Ximing Wang, Lin Cao, John Schwartz, Jorge Hernandez, Gustavo Rodriguez, Brent Liu

Proceedings Volume 10579, 1057913 (2018) https://doi.org/10.1117/12.2296673

KEYWORDS: Picture Archiving and Communication System, Cameras, Algorithm development, Image analysis, Image classification, Neural networks, Pathology, Human-machine interfaces, Databases, Image resolution

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