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e-journal

A Collaborative Biomedical Image-Mining Framework: Application on the Image Analysis of Microscopic Kidney Biopsies

Theodosis Goudas - Nama Orang; Charalampos Doukas - Nama Orang; Aristotle Chatziioannou - Nama Orang; Ilias Maglogiannis - Nama Orang;

Abstract—The analysis and characterization of biomedical image data is a complex procedure involving several processing phases, such as data acquisition, preprocessing, segmentation, feature extraction, and classification. The proper combination and parameterization of the utilized methods are heavily relying on the given image dataset and experiment type. They may thus necessitate advanced image processing and classification knowledge and skills from the side of the biomedical expert. In this study, an application, exploiting web services and applying ontological modeling, is presented, to enable the intelligent creation of imagemining workflows. The described tool can be directly integrated to the RapidMiner, Taverna or similar workflow management platforms. A case study dealing with the creation of a sample workflow for the analysis of kidney biopsy microscopy images is presented to demonstrate the functionality of the proposed framework. Index Terms—Classification, image microscopy, image mining, intelligent planning, kidney biopsies, workflow manager.


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Informasi Detail
Judul Seri
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No. Panggil
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Penerbit
: IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS., 2013
Deskripsi Fisik
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, VOL. 17, NO. 1, JANUARY 2013
Bahasa
English
ISBN/ISSN
1089-7771
Klasifikasi
NONE
Tipe Isi
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Tipe Media
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Tipe Pembawa
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Edisi
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Subjek
TEKNOLOGI KEDOKTERAN
Info Detail Spesifik
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Pernyataan Tanggungjawab
Nurasmi
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Lampiran Berkas
  • A Collaborative Biomedical Image-Mining Framework: Application on the Image Analysis of Microscopic Kidney Biopsies
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