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Imaging

EyePAC

HTIC’s Eye-PAC™ powers computational intelligence capabilities of indigenous low-cost eye screening device 3nethra (more than 1000 installations worldwide, 1.7 million eyes screened). Eye-PAC™  technology consists of image computing and analytics built upon advanced mathematical and computational techniques. The processing, computing, and analytics modules of Eye-PAC™ can be used to develop a range of applications such as disease screening systems, computational platforms for ophthalmic devices, and tools for clinical research and analytics. 
 

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Virtual patient-specific plate contouring for mandible resection

Slicer module developed for automatic bone segmentation, lateral mirroring, contour definition, generates metric instructions for pre-op plate bending. Hardware tool to execute the bending instructions developed.

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Gigapixel neurohistology pipeline for mouse brain connectomics

Web tools for interactive remote compute on demand at gigapixel scale. Automation pipeline for atlas based segmentation and volumetric (teravoxel) analysis. Evolution into cancer digital histopathology automation

Publications & Patents:

 

  1. Gupta, Garima, S. Kulasekaran, Keerthi Ram, Niranjan Joshi, Mohanasankar Sivaprakasam, and Rashmin Gandhi. "Local characterization of neovascularization and identification of proliferative diabetic retinopathy in retinal fundus images." Computerized Medical Imaging and Graphics 55 (2017): 124-132.

  2. John, Sheila, K. Ram, Mohanasankar Sivaprakasam, and Rajiv Raman. "Assessment of Computer-Assisted Screening Technology for Diabetic Retinopathy Screening in India-Preliminary Results and Recommendations from a Pilot Study." Studies in health technology and informatics 231 (2016): 74-81.

  3. Shankaranarayana, Sharath M., Keerthi Ram, Anand Vinekar, Kaushik Mitra, and Mohanasankar Sivaprakasam. "Restoration of Neonatal Retinal Images." (2016)

  4. Shankaranarayana, Sharath M., Keerthi Ram, Kaushik Mitra, and Mohanasankar Sivaprakasam. "Joint Optic Disc and Cup Segmentation Using Fully Convolutional and Adversarial Networks." In Fetal, Infant and Ophthalmic Medical Image Analysis, pp. 168-176. Springer, Cham, 2017.

  5. Kim, Yongsoo, Guangyu Robert Yang, Kith Pradhan, Kannan Umadevi Venkataraju, Mihail Bota, Luis Carlos García del Molino, Greg Fitzgerald et al. "Brain-wide maps reveal stereotyped cell-type-based cortical architecture and subcortical sexual dimorphism." Cell 171, no. 2 (2017): 456-469.

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