Literature DB >> 2194742

A review on biomedical image processing and future trends.

A P Dhawan1.   

Abstract

The last two decades have witnessed a revolutionary development in the field of biomedical and diagnostic imaging. Imaging procedures and modalities which were only in the experimental research phase in the early part of the last two decades, have now become universally accepted clinical procedures. They include computerized tomography (CT), magnetic resonance imaging, ultrasound imaging, nuclear medicine imaging, computerized hematological cell analysis, etc. In the past, the conventional and relatively simple image processing techniques such as image enhancement, gray-level mapping, spectral analysis, region extraction, etc. have been modified for biomedical images and successfully applied for processing and analysis. The role of image enhancement, gray-level mapping, and image reconstruction from projections algorithms in CT and other radiological imaging modalities is well evident. Recently, many advances in biomedical image processing, analysis, and understanding algorithms have shown a great potential for enhancing and interpreting useful diagnostic information from these images more accurately. This paper presents a review on the current state-of-the-art techniques in biomedical image processing and comments on future trends.

Mesh:

Year:  1990        PMID: 2194742     DOI: 10.1016/0169-2607(90)90001-p

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  3 in total

1.  Functional activity maps based on significance measures and Independent Component Analysis.

Authors:  F J Martínez-Murcia; J M Górriz; J Ramírez; C G Puntonet; I A Illán
Journal:  Comput Methods Programs Biomed       Date:  2013-05-06       Impact factor: 5.428

2.  Mathematical morphology-based approach to the enhancement of morphological features in medical images.

Authors:  Yoshitaka Kimori
Journal:  J Clin Bioinforma       Date:  2011-12-16

3.  A Polylobar Nucleus Identifying and Extracting Method for Leukocyte Counting.

Authors:  Jin Chen; Yiping Cao; Jie Gao; Haihua An
Journal:  Comput Math Methods Med       Date:  2021-07-22       Impact factor: 2.238

  3 in total

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