Multi-scale Convolutional Neural Networks for Lung Nodule Classification

	Multi-scale Convolutional Neural Networks for Lung Nodule Classification
	Shen W(沈伟)1 ; Mu Zhou 3; Feng Yang 2; Caiyun Yang1 ; Jie Tian1 ; Tian J(田捷)
	2015
Conference Name	Information Processing in Medical Imaging
Source Publication	IPMI
Conference Date	2015-6
Conference Place	Sabhal Mor Ostaig College on the Isle of Skye, Scotland
Abstract	We investigate the problem of diagnostic lung nodule classification using thoracic Computed Tomography (CT) screening. Unlike traditional studies primarily relying on nodule segmentation for regional analysis, we tackle a more challenging problem on directly modelling raw nodule patches without any prior denition of nodule morphology. We propose a hierarchical learning framework--Multi-scale Convolutional Neural Networks (MCNN)--to capture nodule heterogeneity by extracting discriminative features from alternatingly stacked layers. In particular, to suffciently quantify nodule characteristics, our framework utilizes multi-scale nodule patches to learn a set of class-specic features simultaneously by concatenating response neuron activations obtained at the last layer from each input scale. We evaluate the proposed method on CT images from Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), where both lung nodule screening and nodule annotations are provided. Experimental results demonstrate the effectiveness of our method on classifying malignant and benign nodules without nodule segmentation.
Keyword	Lung Nodule Classification Computed Tomography Imaging Convolutional Neural Networks Computer-aided Diagnoses
Indexed By	EI
Document Type	会议论文
Identifier	http://ir.ia.ac.cn/handle/173211/11699
Collection	中国科学院分子影像重点实验室
Corresponding Author	Tian J(田捷)
Affiliation	1.Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, Institute of Automation, Chinese Academy of Sciences 2.School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China 3.Department of Computer Science and Engineering, University of South Florida, Tampa, United States
First Author Affilication	Institute of Automation, Chinese Academy of Sciences
Recommended Citation GB/T 7714	Shen W,Mu Zhou,Feng Yang,et al. Multi-scale Convolutional Neural Networks for Lung Nodule Classification[C],2015.

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