Rijul Soans

Effective and Enjoyable Ophthalmic Diagnosis: 3D Motion Perception through a Multi-Modal Approach


1. Prof. Dr. F.W.Cornelissen (www.visualneuroscience.nl)

2. Dr. Tapan Gandhi (http://www.tapangandhi.com/)

Background & Interests
I am Rijul Soans from India. I did my Bachelors in Electronics & Communications from Visvesvaraya Technological University, India. Here, I worked on a method that embeds a robust imperceptible watermark in videos that can be recovered back – irrespective of changes in the video resolution or the timeline. Subsequently, I did my Masters in Biomedical Engineering from Manipal University, India. Here, I developed algorithms that detect, segment and classify Tuberculosis bacilli in sputum-smeared microscope images. Next, I worked as a Research Intern at Manipal University and in collaboration with the Indian Institute of Science, India – wherein I expanded my Masters work to develop algorithms that handle Tuberculosis morphotypes, clumps and staining artefacts. Currently, I am pursuing a collaborative PhD in Visual Neuroscience involving the University of Groningen, Indian Institute of Technology – Delhi and All India Institute of Medical Sciences – Delhi. My interests include Eye tracking, Virtual Reality, functional MRI, Deep Learning and Signal/Image Processing.

Aim of the project
One of the goals in the Ophthalmic and Vision sciences is to come up with new, easy and sensitive tools to diagnose the presence of eye disorders. Current tools – for example, perimetry to chart the visual field – are laborious, expensive and cannot be employed in all patient groups (such as the elderly and children). Here, I want to study 3D motion perception with new and affordable Virtual Reality (VR) equipment in combination with gaze-tracking and functional magnetic resonance imaging (fMRI). While there are indications that 2D motion perception is impaired in Glaucoma, the effect of 3D motion perception in the disease is still underexplored. On the other hand, in eye disorders such as Strabismus – current tools measure only static features and do not take into account the dynamic mechanisms of the eye. Therefore, my two-pronged goal is to obtain excellent diagnostic information from dynamic perceptions of the eye, besides making the tests enjoyable by minimizing the use of attention-demanding tasks.

Personal links
1. Linkedin: https://in.linkedin.com/in/rijulsoans
2. Researchgate:  https://www.researchgate.net/profile/Rijul_Soans