Title :
Pneumoconiosis´s Gross Tissue Imaging Classification Based on Morphological Feature Description
Author :
Linying Yu ; Delie Ming ; Liping Xiao
Author_Institution :
State Key Lab. for Multi-spectral Inf. Process. Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
Referring to pneumoconiosis´s gross tissue imaging classification, it is fatal to know the importance of distinguishing lung nodule from macule and how many nodules and macule the pneumoconiosis´s gross tissue image really get. in achieving the distinguishing and counting results, the morphology processing method and some auxiliary digital image processing methods are adopted. after processing, the statistic work begins. the statistic results of abundant candidate parameters give us the chance to pick the parameter performing extremely well. in that way, the classification of pneumoconiosis´s gross tissue images is quite feasible.
Keywords :
biological tissues; diseases; feature extraction; image classification; lung; medical image processing; auxiliary digital image processing methods; lung nodule; macule; morphological feature description; morphology processing method; pneumoconiosis gross tissue imaging classification; Approximation methods; Histograms; Image edge detection; Image segmentation; Lungs; Pathology; Standards; Otsu segmentation; center extraction; lung nodule and macule; morphology; pneumoconiosis; sobel;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-2646-9
DOI :
10.1109/ISCID.2012.157