Cited by 177Radiomics and Machine Learning in Medical ImagingImage Retrieval and Classification TechniquesMedical Image Segmentation Techniques

Feature-Based Image Patch Approximation for Lung Tissue Classification

Yang Song, Weidong Cai, Yun Zhou, Feng, D. D.·2013·IEEE Transactions on Medical Imaging

Abstract

In this paper, we propose a new classification method for five categories of lung tissues in high-resolution computed tomography (HRCT) images, with feature-based image patch approximation. We design two new feature descriptors for higher feature descriptiveness, namely the rotation-invariant Gabor-local binary patterns (RGLBP) texture descriptor and multi-coordinate histogram of oriented gradients (MCHOG) gradient descriptor. Together with intensity features, each image patch is then labeled based on its feature approximation from reference image patches. And a new patch-adaptive sparse approximation (PASA) method is designed with the following main components: minimum discrepancy criteria for sparse-based classification, patch-specific adaptation for discriminative approximation, and feature-space weighting for distance computation. The patch-wise labelings are then accumulated as probabilistic estimations for region-level classification. The proposed method is evaluated on a publicly available ILD database, showing encouraging performance improvements over the state-of-the-arts.

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Crossref · 10.1109/tmi.2013.2241448

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Authors
Song, Y., Cai, W., Zhou, Y., & Feng, D. D.
Affiliations
  • The University of Sydney (AU)
  • Johns Hopkins University (US)
Venue
IEEE Transactions on Medical Imaging
Published
2013-04
Volume
32
Issue
4
Pages
797-808
ISSN
  • 0278-0062 (ISSN-L)
  • 1558-254X
OpenAlex
W1975020933
Cited by
177
References
38
Citations by year
2026: 1 · 2025: 13 · 2024: 5 · 2023: 14 · 2022: 11 · 2021: 11 · 2020: 13 · 2019: 16 · 2018: 21 · 2017: 22 · 2016: 17 · 2015: 15 · 2014: 14 · 2013: 4
FWCI
12.91
Type
journal article
Language
en
Open access
closed
Locations
  • IEEE Transactions on Medical Imaging (publishedVersion)
  • PubMed (publishedVersion)
  • PolyU Institutional Research Archive (Hong Kong Polytechnic University) (submittedVersion)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
Keywords
lung tissue classification, high-resolution computed tomography, sparse approximation, texture features, interstitial lung disease
MeSH terms
Algorithms, Humans, Image Processing, Computer-Assisted, Lung, Models, Biological, Tomography, X-Ray Computed, Databases, Factual, Lung Diseases, Interstitial

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