Computational Imaging & VisAnalysis

#201: A. Haridas, F. Bunyak, and K. Palaniappan

Interactive segmentation relabeling for classification of whole-slide histopathology imagery

IEEE Int. Symposium on Computer-Based Medical Systems (CBMS), pgs. 84-87, 2015

visualization, big data, biomedical, histopathology

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@inproceedings{Haridas:CBMS-2015,
  author = "A. Haridas and F. Bunyak and K. Palaniappan",
  title = "Interactive segmentation relabeling for classification of whole-slide histopathology imagery",
  year = 2015,
  booktitle = "IEEE Int. Symposium on Computer-Based Medical Systems (CBMS)",
  pages = "84-87",
  month = "Jun",
  keywords = "visualization, big data, biomedical, histopathology",
  doi = "10.1109/CBMS.2015.89",
  url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7167462"
}

A. Haridas, F. Bunyak, and K. Palaniappan. Interactive segmentation relabeling for classification of whole-slide histopathology imagery. IEEE Int. Symposium on Computer-Based Medical Systems (CBMS), pages 84-87, June 2015.

#215: F. Bunyak, A. Hafiane, Z. Al-Milagi, I. Ersoy, A. Haridas, and K. Palaniappan

A segmentation-based multi-scale framework for the classification of epithelial and stromal tissues in H&E images

Proc. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pgs. 450-453, 2015

biomedical, histopathology, segmentation, classification

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar

@inproceedings{Bunyak:histo-seg-2015,
  author = "F. Bunyak and A. Hafiane and Z. Al-Milagi and I. Ersoy and A. Haridas and K. Palaniappan",
  title = "A segmentation-based multi-scale framework for the classification of epithelial and stromal tissues in H&E images",
  year = 2015,
  booktitle = "Proc. IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
  pages = "450-453",
  keywords = "biomedical, histopathology, segmentation, classification",
  url = "http://cci.drexel.edu/ieeebibm/bibm2015/index.html"
}

F. Bunyak, A. Hafiane, Z. Al-Milagi, I. Ersoy, A. Haridas, and K. Palaniappan. A segmentation-based multi-scale framework for the classification of epithelial and stromal tissues in H&E images. Proc. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pages 450-453, 2015.

#168: J. Fraser, A. Haridas, G. Seetharaman, R. Rao, and K. Palaniappan

KOLAM: A cross-platform architecture for scalable visualization and tracking in wide-area motion imagery

Proc. SPIE Conf. Geospatial InfoFusion III (Defense, Security and Sensing: Sensor Data and Information Exploitation), Volume 8747, pgs. 87470N, 2013

visualization, big data, wami, tracking, fmv, features, motion, dod, biomedical

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar

KOLAM is an open, cross-platform, interoperable, scalable and extensible framework supporting a novel multi- scale spatiotemporal dual-cache data structure for big data visualization and visual analytics. This paper focuses on the use of KOLAM for target tracking in high-resolution, high throughput wide format video also known as wide-area motion imagery (WAMI). It was originally developed for the interactive visualization of extremely large geospatial imagery of high spatial and spectral resolution. KOLAM is platform, operating system and (graphics) hardware independent, and supports embedded datasets scalable from hundreds of gigabytes to feasibly petabytes in size on clusters, workstations, desktops and mobile computers. In addition to rapid roam, zoom and hyper- jump spatial operations, a large number of simultaneously viewable embedded pyramid layers (also referred to as multiscale or sparse imagery), interactive colormap and histogram enhancement, spherical projection and terrain maps are supported. The KOLAM software architecture was extended to support airborne wide-area motion imagery by organizing spatiotemporal tiles in very large format video frames using a temporal cache of tiled pyramid cached data structures. The current version supports WAMI animation, fast intelligent inspection, trajectory visualization and target tracking (digital tagging); the latter by interfacing with external automatic tracking software. One of the critical needs for working with WAMI is a supervised tracking and visualization tool that allows analysts to digitally tag multiple targets, quickly review and correct tracking results and apply geospatial visual analytic tools on the generated trajectories. One-click manual tracking combined with multiple automated tracking algorithms are available to assist the analyst and increase human effectiveness. Keywords: wide-area motion imagery, WAMI, digital tagging, assisted tracking, trajectory visualization, tra- jectory data mining, spatiotemporal cache, multiresolution tiled pyramid imagery

@inproceedings{Fraser:KOLAM_SPIE-2013,
  author = "J. Fraser and A. Haridas and G. Seetharaman and R. Rao and K. Palaniappan",
  title = "KOLAM: A cross-platform architecture for scalable visualization and tracking in wide-area motion imagery",
  year = 2013,
  booktitle = "Proc. SPIE Conf. Geospatial InfoFusion III (Defense, Security and Sensing: Sensor Data and Information Exploitation)",
  volume = 8747,
  pages = "87470N",
  keywords = "visualization, big data, wami, tracking, fmv, features, motion, dod, biomedical",
  doi = "10.1117/12.2018162"
}

J. Fraser, A. Haridas, G. Seetharaman, R. Rao, and K. Palaniappan. KOLAM: A cross-platform architecture for scalable visualization and tracking in wide-area motion imagery. Proc. SPIE Conf. Geospatial InfoFusion III (Defense, Security and Sensing: Sensor Data and Information Exploitation), volume 8747, pages 87470N, 2013.

#123: A. Haridas, R. Pelapur, J. Fraser, F. Bunyak, and K. Palaniappan

Visualization of automated and manual trajectories in wide-area motion imagery

15th Int. Conf. Information Visualization, pgs. 288--293, 2011

visualization, big data, wami, tracking, fmv, features, motion, dod

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@inproceedings{Haridas:InfoVis-2011,
  author = "A. Haridas and R. Pelapur and J. Fraser and F. Bunyak and K. Palaniappan",
  title = "Visualization of automated and manual trajectories in wide-area motion imagery",
  year = 2011,
  booktitle = "15th Int. Conf. Information Visualization",
  pages = "288--293",
  keywords = "visualization, big data, wami, tracking, fmv, features, motion, dod",
  doi = "10.1109/IV.2011.67",
  url = "http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6004056"
}

A. Haridas, R. Pelapur, J. Fraser, F. Bunyak, and K. Palaniappan. Visualization of automated and manual trajectories in wide-area motion imagery. 15th Int. Conf. Information Visualization, pages 288--293, 2011.

#114: K. Palaniappan, F. Bunyak, P. Kumar, I. Ersoy, S. Jaeger, K. Ganguli, A. Haridas, J. Fraser, R. Rao, and G. Seetharaman

Efficient feature extraction and likelihood fusion for vehicle tracking in low frame rate airborne video

13th Int. Conf. Information Fusion, 2010

wami, tracking, fmv, motion, features, fusion, dod

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@inproceedings{Pal:Fusion-2010,
  author = "K. Palaniappan and F. Bunyak and P. Kumar and I. Ersoy and S. Jaeger and K. Ganguli and A. Haridas and J. Fraser and R. Rao and G. Seetharaman",
  title = "Efficient feature extraction and likelihood fusion for vehicle tracking in low frame rate airborne video",
  year = 2010,
  booktitle = "13th Int. Conf. Information Fusion",
  keywords = "wami, tracking, fmv, motion, features, fusion, dod",
  doi = "10.1109/ICIF.2010.5711891",
  url = "http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5711891"
}

K. Palaniappan, F. Bunyak, P. Kumar, I. Ersoy, S. Jaeger, K. Ganguli, A. Haridas, J. Fraser, R. Rao, and G. Seetharaman. Efficient feature extraction and likelihood fusion for vehicle tracking in low frame rate airborne video. 13th Int. Conf. Information Fusion, 2010.

5 Publications by "A. Haridas"

Interactive segmentation relabeling for classification of whole-slide histopathology imagery

visualization, big data, biomedical, histopathology

A segmentation-based multi-scale framework for the classification of epithelial and stromal tissues in H&E images

biomedical, histopathology, segmentation, classification

KOLAM: A cross-platform architecture for scalable visualization and tracking in wide-area motion imagery

visualization, big data, wami, tracking, fmv, features, motion, dod, biomedical

Visualization of automated and manual trajectories in wide-area motion imagery

visualization, big data, wami, tracking, fmv, features, motion, dod

Efficient feature extraction and likelihood fusion for vehicle tracking in low frame rate airborne video

wami, tracking, fmv, motion, features, fusion, dod