Image-based Volume Segmentation

Image-Based Volume Segmentation is a computational method that partitions three-dimensional volumetric data into meaningful regions or structures based on intensity, texture, and spatial information derived directly from acquired imaging modalities, distinguishing it from non-image-based or synthetically guided segmentation approaches.

192

Publications

7.9K

Citations

1K

Authors

428

Institutions

Publications per year

2017–2026

82

Authors

1K

  1. AF
    Aaron Fenster

    Western University, Canada

    4 publications · 132 citations

    4

    h-index

  2. PH
    Pheng‐Ann Heng

    Chinese University of Hong Kong, Hong Kong SAR China

    4 publications · 299 citations

    4

    h-index

  3. JE
    Jan Egger

    Graz University of Technology, Austria

    3 publications · 177 citations

    3

    h-index

  4. YZ
    Yefeng Zheng

    Tencent (China), China

    3 publications · 187 citations

    3

    h-index

  5. MJ
    María J. Ledesma‐Carbayo

    Universidad Politécnica de Madrid, Spain

    3 publications · 80 citations

    3

    h-index

1–5 of 1K

Venues

  1. 10

    h-index

  2. Medical Image Analysis

    9 publications · 534 citations

    9

    h-index

  3. IEEE Transactions on Medical Imaging

    8 publications · 860 citations

    8

    h-index

  4. NeuroImage

    7 publications · 512 citations

    7

    h-index

  5. Lecture notes in computer science

    LNCS · Book series · 6 publications · 186 citations

    6

    h-index

1–5