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Spatially-constrained probability distribution model of incoherent motion (SPIM) for abdominal diffusion-weighted MRI

Publication: Journal Article

Kurugol, Sila, Moti Freiman, Onur Afacan, Jeannette Perez-Rossello, Michael Callahan, and Simon Warfield. 2016. “Spatially-Constrained Probability Distribution Model of Incoherent Motion (SPIM) for Abdominal Diffusion-Weighted MRI”. Medical Image Analysis 32: 173–183.

Automatic renal segmentation in DCE-MRI using convolutional neural networks

Publication: Conference Paper

Haghighi, Marzieh, Simon Warfield, and Sila Kurugol. 2018. “Automatic Renal Segmentation in DCE-MRI Using Convolutional Neural Networks”. In 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 1534–1537. IEEE.

C37 COPD: WHAT IS NEW IN IMAGING?: Ranking Of Emphysema Patterns Into Monotonic Disease Progression Levels Using Local Density Histograms In Chest CT Scans

Publication: Journal Article

Kurugol, Diaz, Washko, and San Jose Estepar. 2014. “C37 COPD: WHAT IS NEW IN IMAGING?: Ranking Of Emphysema Patterns Into Monotonic Disease Progression Levels Using Local Density Histograms In Chest CT Scans”. American Journal of Respiratory and Critical Care Medicine 189: 1.

Active deep learning with Fisher information for patch-wise semantic segmentation

Publication: Book Chapter

Sourati, Jamshid, Ali Gholipour, Jennifer Dy, Sila Kurugol, and Simon Warfield. 2018. “Active Deep Learning With Fisher Information for Patch-Wise Semantic Segmentation”. In Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 83–91. Springer, Cham.

Curved planar reformatting and convolutional neural network-based segmentation of the small bowel for visualization and quantitative assessment of pediatric Crohn's disease from MRI

Publication: Journal Article

Lamash, Yechiel, Sila Kurugol, Moti Freiman, Jeannette Perez-Rossello, Michael Callahan, Athos Bousvaros, and Simon Warfield. 2019. “Curved Planar Reformatting and Convolutional Neural Network-Based Segmentation of the Small Bowel for Visualization and Quantitative Assessment of Pediatric Crohn’s Disease from MRI”. Journal of Magnetic Resonance Imaging 49 (6): 1565–1576.

Self-navigated bulk motion detection for feed and wrap renal dynamic radial VIBE DCE-MRI

Publication: Conference Paper

Coll-Font, Jaume, Onur Afacan, Alto Stemmer, Richard Lee, Jeanne Chow, Simon Warfield, and Sila Kurugol. 2019. “Self-Navigated Bulk Motion Detection for Feed and Wrap Renal Dynamic Radial VIBE DCE-MRI”. In Proceedings of Int. Soc. Of Magnetic Resonance Imaging, 2019.

Glomerular filtration rate estimation by motion-robust high spatiotemporal resolution DCE-MRI with radial VIBE and comparison with plasma clearance of 99mTc-DTPA

Publication: Journal Article

Kurugol, Sila, Onur Afacan, Alto Stemmer, Richard Lee, Jeanne Chow, and Simon Warfield. 2019. “Glomerular Filtration Rate Estimation by Motion-Robust High Spatiotemporal Resolution DCE-MRI With Radial VIBE and Comparison With Plasma Clearance of 99mTc-DTPA”. Proceedings of Int. Soc. Of Magnetic Resonance Imaging.

Simultaneous Motion and Distortion Correction Using Dual-Echo Diffusion-Weighted MRI

Publication: Journal Article

Afacan, Onur, Scott Hoge, Tess Wallace, Ali Gholipour, Sila Kurugol, and Simon Warfield. 2020. “Simultaneous Motion and Distortion Correction Using Dual-Echo Diffusion-Weighted MRI”. Journal of Neuroimaging.

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Dr. Kurugol is an Instructor of Radiology at Harvard Medical School and a principal investigator at the Computational Radiology Lab (CRL) at Boston Children's Hospital. She received her BS from Middle East Technical University (METU), MS from Bilkent University, Ankara, Turkey, and PhD from...

3D level set esophagus segmentation in thoracic ct images using spatial, appearance and shape models

Publication: Conference Paper

Kurugol, Sila, Jennifer Dy, Gregory Sharp, and Dana Brooks. 2010. “3D Level Set Esophagus Segmentation in Thoracic Ct Images Using Spatial, Appearance and Shape Models”. In 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 444–447. IEEE.