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Apply convolutional neural network to lung nodule detection: Recent progress and challenges

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Convolutional Neural Network has shown great success in many areas. Different from the hand-engineered feature based classification, Convolutional Neural Network uses self-learned features from data for classification. Recently, some progress has been made in the area of Convolutional Neural Network based lung nodule detection. This paper gives a brief introduction to the problems in such area reviews the recent related results, and concludes the challenges met. Besides some technical details, we also introduce some available public packages for a fast development and some public data sources.

Original languageEnglish
Title of host publicationSmart Health - International Conference, ICSH 2017, Proceedings
EditorsElena Karahanna, Indranil Bardhan, Hsinchun Chen, Daniel Dajun Zeng
PublisherSpringer Verlag
Pages214-222
Number of pages9
ISBN (Print)9783319679631
DOIs
StatePublished - 2017
EventInternational Conference on Smart Health, ICSH 2017 - Hong Kong, Hong Kong
Duration: Jun 26 2017Jun 27 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10347 LNCS

Conference

ConferenceInternational Conference on Smart Health, ICSH 2017
Country/TerritoryHong Kong
CityHong Kong
Period06/26/1706/27/17

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