Naga Karthik Enamundram

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Hi there! I’m Naga, a fourth-year PhD student at NeuroPoly, Polytechnique Montréal. I’m also affiliated to Mila - Québec AI Institute. During my PhD, I worked on developing deep learning-based methods for medical image analysis, with a particular focus on improving the estimation of imaging biomarkers using real-world spinal cord imaging data. I have developed automatic tools for segmentation of the spinal cord and lesions across various MRI contrasts and pathologies such as spinal cord injury (SCI), multiple sclerosis (MS) and degenerative cervical myelopathy (DCM). I have also experimented with generative modelling, in particular, training GANs for cross-modality MR-CT synthesis and diffusion models for synthesizing spinal cord lesions. In the past, I have also worked on the application of continual/lifelong learning methods for the segmentation of brain MS lesions. Please head to my Google Scholar profile for a complete list of my publications.

When I am not working, you’ll find me either running :running:, hiking :mountain:, or reading :book:.

news

Jul 25, 2025 Our paper “Dynamic Robot-Assisted Surgery with Hierarchical Class-Incremental Semantic Segmentation” was accepted at MICCAI workshop on Applications of Medical Artificial Intelligence (AMAI) 2025 in Daejon, South Korea! 🇰🇷
Mar 13, 2025 I was featured in the UNIQUE-Québec Newsletter as part of their student spotlight series! Please find the newsletter here. 📰
Jan 13, 2025 Our paper “Towards contrast-agnostic soft segmentation of the spinal cord” was accepted at the Medical Image Analysis journal (Impact Factor: 10.7)! 🎉
Jul 19, 2024 Our paper “SCIsegV2: A Universal Tool for Segmentation of Intramedullary Lesions in Spinal Cord Injury” was accepted at MICCAI Applications of Medical Artificial Intelligence (AMAI) Workshop 2024 in Marrakech, Morocco! 🇲🇦
Mar 07, 2024 I was awarded the DAAD Short-term Research Grant for a 4-month research stay at the Technical University of Munich, Germany! 🥨 🇩🇪
Feb 02, 2024 Our recent works on contrast-agnostic spinal cord segmentation and segmentation of spinal cord injury lesions were accepted for Oral Presentations at the 2024 ISMRM & ISMRT Annual Meeting & Exhibition in Singapore :singapore: !
Nov 22, 2023 I gave a talk on Automatic Segmentation of Brain and Spinal Cord Lesions across Pathologies at the UNIQUE Fellows Get-Together, held at Mila!
Jun 05, 2022 Honoured to receive the Governor General of Canada’s Academic Gold Medal for outstanding academic achievements during my master’s at ÉTS! 🏅 🇨🇦

selected publications

  1. arXiv
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    Monitoring morphometric drift in lifelong learning segmentation of the spinal cord
    Enamundram Naga Karthik, Sandrine Bédard, Jan Valošek, and 53 more authors
    arXiv, 2025
  2. Imaging Neuroscience
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    Automatic segmentation of spinal cord lesions in MS: A robust tool for axial T2-weighted MRI scans
    Enamundram Naga Karthik*, Julian McGinnis*, Ricarda Wurm, and 17 more authors
    Imaging Neuroscience, Jun 2025
    *shared first authorship
  3. MedIA
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    Towards contrast-agnostic soft segmentation of the spinal cord
    Sandrine Bédard*, Enamundram Naga Karthik*, Charidimos Tsagkas, and 5 more authors
    Medical Image Analysis, Jun 2025
    *shared first authorship
  4. Radiology: AI
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    SCIseg: Automatic Segmentation of Intramedullary Lesions in Spinal Cord Injury on T2-weighted MRI Scans
    Enamundram Naga Karthik*, Jan Valošek*, Andrew C. Smith, and 6 more authors
    Radiology: Artificial Intelligence, Jun 2025
    *shared first authorship
  5. MELBA
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    Label fusion and training methods for reliable representation of inter-rater uncertainty
    Andreanne Lemay, Charley Gros, Enamundram Naga Karthik, and 1 more author
    Machine Learning for Biomedical Imaging, Jun 2022