Paper Info
Title
Pathological Image Analysis Using the GPU: Stroma Classification for Neuroblastoma
Abstract
Neuroblastoma is one of the most malignant childhood cancers affecting infants mostly. The current prognosis is based on microscopic examination of slides by expert pathologists, a process that is error-prone, time consuming and may lead to inter- and intra-reader variations. Therefore, we are developing a Computer Aided Prognosis (CAP) system which provides computerized image analysis t o assist pathologist in their prognosis. Since this system operates on relatively largescale images and requires sophisticated algorithms, it takes a long time to process whole-slide images. I n this paper, we propose a novel and eficient approach for the execution of a CAP system for neuroblastoma prognosis, using the graphics processing unit (GPU). B y leveraging high memory bandwidth and strong floating point operation capabilities of the GPU, our goal is t o achieve order of magnitude reduction in the overall execution time as compared t o that on a CPU alone. The proposed approach was tested on a set of testing images with a promising accuracy of 99.4% and an execution performance gain factor up to 45 times compared t o C++ code running on the CPU.
Year
DOI
Venue
2007
10.1109/BIBM.2007.56
Fremont, CA
Keywords
Field
DocType
pathological image analysis,stroma classification,eficient approach,cap system,overall execution time,long time,neuroblastoma prognosis,execution performance gain factor,current prognosis,o c,time consuming,neurophysiology,paediatrics,image classification,memory bandwidth,floating point,image analysis,cancer,computer graphics
Central processing unit,Computer-aided,Floating point,High memory,Computer science,Image processing,Bioinformatics,Contextual image classification,Graphics processing unit,Computer graphics
Conference
ISSN
ISBN
Citations 
2156-1125
0-7695-3031-1
16
PageRank 
References 
Authors
1.31
8
6
Name
Order
Citations
PageRank
Antonio Ruiz11018.22
Olcay Sertel235124.21
Manuel Ujaldon324426.71
umit v catalyurek41405101.09
Joel H. Saltz54046569.91
Metin Gurcan6564.28