no code implementations • 7 Nov 2021 • Rahul Bishain, Bhismadev Chakrabarti, Jayashree Dasgupta, Indu Dubey, Sharat Chandran
Screening for any of the Autism Spectrum Disorders is a complicated process often involving a hybrid of behavioural observations and questionnaire based tests.
no code implementations • 23 Dec 2019 • Preeti Gopal, Sharat Chandran, Imants Svalbe, Ajit Rajwade
Our results on 3D data show that prior information can be used to compensate for the low-dose artefacts, and we demonstrate that it is possible to simultaneously prevent the prior from adversely biasing the reconstructions of new changes in the test object, via a method called ``re-irradiation''.
no code implementations • 11 Sep 2019 • Preeti Gopal, Sharat Chandran, Imants Svalbe, Ajit Rajwade
While this is easily feasible when measurements are acquired from a large number of projection views, it is challenging when the number of views is limited.
no code implementations • 23 Dec 2018 • Preeti Gopal, Sharat Chandran, Imants Svalbe, Ajit Rajwade
The need for tomographic reconstruction from sparse measurements arises when the measurement process is potentially harmful, needs to be rapid, or is uneconomical.
1 code implementation • 4 Jan 2018 • Rahul Mitra, Nehal Doiphode, Utkarsh Gautam, Sanath Narayan, Shuaib Ahmed, Sharat Chandran, Arjun Jain
Similarly on the Strecha dataset, we see an improvement of 3-5% for the matching task in non-planar scenes.
no code implementations • 6 Dec 2017 • Preeti Gopal, Ritwick Chaudhry, Sharat Chandran, Imants Svalbe, Ajit Rajwade
Recent research in tomographic reconstruction is motivated by the need to efficiently recover detailed anatomy from limited measurements.
no code implementations • 24 Jan 2017 • Rahul Mitra, Jiakai Zhang, Sanath Narayan, Shuaib Ahmed, Sharat Chandran, Arjun Jain
Scenes from the Oxford ACRD, MVS and Synthetic datasets are used for evaluating the patch matching performance of the learnt descriptors while the Strecha dataset is used to evaluate the 3D reconstruction task.