Prof. Mona K. Garvin
Associate Prof of Electrical and Computer Engg at The Univ. of Iowa
SPIE Involvement:
Conference Program Committee | Author | Instructor
Publications (26)

Proceedings Article | 4 April 2022 Poster + Presentation + Paper
Proceedings Volume 12036, 1203622 (2022) https://doi.org/10.1117/12.2611850
KEYWORDS: Blood circulation, Retina, Eye, Blood, Laser speckle imaging

Proceedings Article | 4 April 2022 Presentation + Paper
Hui Xie, Jui-Kai Wang, Randy Kardon, Mona Garvin, Xiaodong Wu
Proceedings Volume 12032, 120320W (2022) https://doi.org/10.1117/12.2611859
KEYWORDS: Optical coherence tomography, Image segmentation, Neural networks, 3D image processing, Retina

SPIE Journal Paper | 19 November 2015
Qiao Hu, Michael Abràmoff, Mona K. Garvin
JMI, Vol. 2, Issue 04, 044001, (November 2015) https://doi.org/10.1117/12.10.1117/1.JMI.2.4.044001
KEYWORDS: Image classification, Image segmentation, Head, Veins, Arteries, Optimization (mathematics), Visualization, Algorithm development, Detection and tracking algorithms, Feature extraction

Proceedings Article | 20 March 2015 Paper
Jui-Kai Wang, Randy Kardon, Mona Garvin
Proceedings Volume 9413, 94133V (2015) https://doi.org/10.1117/12.2081485
KEYWORDS: Image segmentation, Optical coherence tomography, Raster graphics, Image registration, Visibility, 3D image processing, Optic nerve, Visualization, Retina, Head

Proceedings Article | 20 March 2015 Paper
Proceedings Volume 9414, 94140F (2015) https://doi.org/10.1117/12.2081423
KEYWORDS: Image segmentation, Optic nerve, Photography, Optical coherence tomography, Feature extraction, Head, Optical testing, 3D image processing, 3D metrology, Eye

Showing 5 of 26 publications
Conference Committee Involvement (16)
Image Processing
17 February 2025 | San Diego, California, United States
Image Processing
19 February 2024 | San Diego, California, United States
Image Processing
20 February 2023 | San Diego, California, United States
Image Processing
20 February 2022 | San Diego, California, United States
Image Processing
15 February 2021 | Online Only, California, United States
Showing 5 of 16 Conference Committees
Course Instructor
SC1026: Graph Algorithmic Techniques for Biomedical Image Segmentation
This course provides an in-depth overview of two state-of-the-art graph-based methods for segmenting three-dimensional structures in medical images: graph cuts and the LOGISMOS (Layered Optimal Graph Image Segmentation of Multiple Objects and Surfaces) approach. Such graph-based approaches are becoming increasingly used in the medical image analysis community, in part, due to their ability to efficiently produce globally optimal three-dimensional segmentations in a single pass (not requiring an iterative numerical scheme). Additionally, LOGISMOS enables the simultaneous optimal detection of multiple surfaces in volumetric images, which is important in many medical image segmentation applications. In the first part of the course, we provide a broad overview of both graph cuts and the LOGISMOS approach, including the presentation of a number of example applications. In the second and third parts of the course, we present the algorithmic details of graph cuts and the LOGISMOS approach, respectively. In the final part of the course, we discuss the design of cost functions, which is of paramount importance in any graph-based approach.
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