High Resolution Digital Tissue Image Processing using Texture Image Databases - Technological Innovation for Cloud-Based Engineering Systems Access content directly
Conference Papers Year : 2015

High Resolution Digital Tissue Image Processing using Texture Image Databases

Abstract

Texture based image databases integrated with effective searching algorithms are useful solutions for many scientific and industrial purposes. Medical image processing of high resolution tissue images is one of the areas, where the cell/tissue classification can rely on such solutions. In this paper we are describing the design, development and usage of a specialized medical texture image database. Our primary aim with this texture database is to provide Digital Imaging and Communication in Medicine (DICOM) compatible texture image dataset for cell, gland and epithelium classification in histology. Our solution includes a Picture Archiving and Communication System (PACS) subsystem, which is mainly provide a communication interface (texture image searching and retrieval) and enables image processing algorithms to work more effectively on high resolution tissue slide images. In this paper we describe how our Local Binary Pattern (LBP) based algorithm benefits texture database usage when solving image processing problems in histology and histopathology.
Fichier principal
Vignette du fichier
336594_1_En_26_Chapter.pdf (4 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01343489 , version 1 (08-07-2016)

Licence

Attribution

Identifiers

Cite

Gábor Kiss, Orsolya Eszter Cseri, Ádám Altsach, István Imre Bándi, Levente Kovács, et al.. High Resolution Digital Tissue Image Processing using Texture Image Databases. 6th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2015, Costa de Caparica, Portugal. pp.239-247, ⟨10.1007/978-3-319-16766-4_26⟩. ⟨hal-01343489⟩
97 View
122 Download

Altmetric

Share

Gmail Facebook X LinkedIn More