Kotagiri Ramamohanarao
Overview
Explore the profile of Kotagiri Ramamohanarao including associated specialties, affiliations and a list of published articles.
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29
Citations
207
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Recent Articles
1.
Zalesky A, Sarwar T, Tian Y, Liu Y, Yeo B, Ramamohanarao K
Netw Neurosci
. 2024 Dec;
8(4):1291-1309.
PMID: 39735518
Several recent studies have optimized deep neural networks to learn high-dimensional relationships linking structural and functional connectivity across the human connectome. However, the extent to which these models recapitulate individual-specific...
2.
Sarwar T, Ramamohanarao K, Daducci A, Schiavi S, Smith R, Zalesky A
Neuroimage
. 2023 Sep;
281:120376.
PMID: 37714389
Tractography algorithms are prone to reconstructing spurious connections. The set of streamlines generated with tractography can be post-processed to retain the streamlines that are most biologically plausible. Several microstructure-informed filtering...
3.
Gou J, Sun L, Yu B, Du L, Ramamohanarao K, Tao D
IEEE Trans Neural Netw Learn Syst
. 2022 Oct;
35(5):6718-6730.
PMID: 36264723
Knowledge distillation (KD), as an efficient and effective model compression technique, has received considerable attention in deep learning. The key to its success is about transferring knowledge from a large...
4.
Sarwar T, Ramamohanarao K, Zalesky A
NMR Biomed
. 2021 Sep;
34(12):e4605.
PMID: 34516016
Diffusion MRI tractography is the most widely used macroscale method for mapping connectomes in vivo. However, tractography is prone to various errors and biases, and thus tractography-derived connectomes require careful...
5.
Al Bkhetan Z, Chana G, Ong C, Goudey B, Ramamohanarao K
Brief Bioinform
. 2021 Apr;
22(5).
PMID: 33834181
Motivation: The high accuracy of recent haplotype phasing tools is enabling the integration of haplotype (or phase) information more widely in genetic investigations. One such possibility is phase-aware expression quantitative...
6.
Al Bkhetan Z, Chana G, Ramamohanarao K, Verspoor K, Goudey B
Brief Bioinform
. 2020 Nov;
22(4).
PMID: 33236761
Haplotype phasing is a critical step for many genetic applications but incorrect estimates of phase can negatively impact downstream analyses. One proposed strategy to improve phasing accuracy is to combine...
7.
Sarwar T, Seguin C, Ramamohanarao K, Zalesky A
Neuroimage
. 2020 Feb;
212:116654.
PMID: 32068163
We propose a new framework to map structural connectomes using deep learning and diffusion MRI. We show that our framework not only enables connectome mapping with a convolutional neural network...
8.
Zalesky A, Sarwar T, Ramamohanarao K
Magn Reson Med
. 2019 Oct;
83(3):791-794.
PMID: 31631374
No abstract available.
9.
Sarwar T, Ramamohanarao K, Zalesky A
Magn Reson Med
. 2018 Oct;
81(2):1368-1384.
PMID: 30303550
Purpose: Human connectomics necessitates high-throughput, whole-brain reconstruction of multiple white matter fiber bundles. Scaling up tractography to meet these high-throughput demands yields new fiber tracking challenges, such as minimizing spurious...
10.
Hussain M, Bhuiyan A, Luu C, Smith R, Guymer R, Ishikawa H, et al.
PLoS One
. 2018 Jun;
13(6):e0198281.
PMID: 29864167
In this paper, we propose a novel classification model for automatically identifying individuals with age-related macular degeneration (AMD) or Diabetic Macular Edema (DME) using retinal features from Spectral Domain Optical...