SHADeS: self-supervised monocular depth estimation through non-Lambertian image decomposition - Top-Institutions - MDSpire

SHADeS: self-supervised monocular depth estimation through non-Lambertian image decomposition

  • By

  • Rema Daher

  • Francisco Vasconcelos

  • Danail Stoyanov

  • May 13, 2025

  • 0 min

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Top Institutions in Surgery

Brief introduction explaining scope and methodology.

  • #1

    Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)
    Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

    Cambridge, MA

    Key Differentiators

    • Medical Image Computing
    • Computer Vision
    • Machine Learning

  • #2

    Johns Hopkins University - Malone Center for Engineering in Healthcare
    Johns Hopkins University - Malone Center for Engineering in Healthcare

    Baltimore, MD

    Key Differentiators

    • Biomedical Engineering
    • Medical Image Analysis
    • Computer-Assisted Interventions

  • #3

    Stanford University - Center for Artificial Intelligence in Medicine & Imaging (AIMI)
    Stanford University - Center for Artificial Intelligence in Medicine & Imaging (AIMI)

    Stanford, CA

    Key Differentiators

    • Artificial Intelligence
    • Medical Imaging
    • Gastroenterology

  • #4

    Imperial College London - Department of Computing and Institute of Global Health Innovation
    Imperial College London - Department of Computing and Institute of Global Health Innovation

    London, N/A

    Key Differentiators

    • Medical Image Computing
    • Computer Vision
    • Endoscopy Technology

  • #5

    Mayo Clinic - Department of Gastroenterology and Biomedical Engineering
    Mayo Clinic - Department of Gastroenterology and Biomedical Engineering

    Rochester, MN

    Key Differentiators

    • Gastroenterology
    • Biomedical Engineering
    • Medical Imaging

Original Source(s)

SHADeS: self-supervised monocular depth estimation through non-Lambertian image decomposition

  • by Rema Daher, Francisco Vasconcelos, Danail Stoyanov

  • May 13, 2025

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