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3D Adaptive Histogram Equalization Method for Medical Volumes

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Author(s):
Amorim, Paulo ; Moraes, Thiago ; Silva, Jorge ; Pedrini, Helio ; Tremeau, A ; Imai, F ; Braz, J
Total Authors: 7
Document type: Journal article
Source: VISAPP: PROCEEDINGS OF THE 13TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS - VOL 4: VISAPP; v. N/A, p. 8-pg., 2018-01-01.
Abstract

Medical imaging plays a fundamental role in the diagnosis and treatment of several diseases, enabling the visualization of internal organs and tissues for use in clinical procedures. The quality of medical images can be degraded by several factors, such as noise and poor contrast. The application of filtering and contrast enhancement techniques is usually necessary to improve the quality of images, which facilitates the segmentation and classification stages. In this paper, we develop and analyze a novel three-dimensional adaptive histogram equalization method for improving contrast in the context of medical imaging. Several data sets are used to demonstrate the effectiveness of the proposed approach. (AU)

FAPESP's process: 17/12646-3 - Déjà vu: feature-space-time coherence from heterogeneous data for media integrity analytics and interpretation of events
Grantee:Anderson de Rezende Rocha
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction?
Grantee:Alexandre Xavier Falcão
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 13/07559-3 - BRAINN - The Brazilian Institute of Neuroscience and Neurotechnology
Grantee:Fernando Cendes
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC