Pulmonary-nodule detection using an ensemble of 3D SE-ReSnet18 and DPN68 models

Or Katz, Dan Presil, Liz Cohen, Yael Schwartzbard, Sarah Hoch, Shlomo Kashani

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

4 Scopus citations


This short paper describes our contribution to the LNDb - Grand Challenge on automatic lung cancer patient management [1]. We only participated in Sub-Challenge A: Nodule Detection. The officially stated goal of this challenge is From chest CT scans, participants must detect pulmonary nodules. We developed a computer-aided detection (CAD) system for the identification of small pulmonary nodules in screening CT scans. The two main modules of our system consist of a CNN based nodule candidate detection, and a neural classifier for false positive reduction. The preliminary results obtained on the challenge database is discussed. In this work, we developed an Ensemble learning pipeline using state of the art convolutional neural networks (CNNs) as base detectors. In particular, we utilize the 3D versions of SE-ResNet18 and DPN68. Much like classical bagging, base learners were trained on 10 stratified data-set folds (the LUNA16 patient-level dataset splits) generated by bootstrapping both our training set (LUNA16) and the challenge provided training set. Furthermore, additional variation was introduced by using different CNN architectures. Particularly, we opted for an exhaustive search of the best detectors, consisting mostly of DPN68 [2] and SE-ResNet18 [3] architectures. We unfortunately joined the competition late, and we did not train our system on the corpus provided by the organizers and therefore we only run inference using our LIDC-IDRI trained model. We do realize this is not the best approach.

Original languageEnglish
Title of host publicationImage Analysis and Recognition - 17th International Conference, ICIAR 2020, Proceedings
EditorsAurélio Campilho, Fakhri Karray, Zhou Wang
Number of pages8
ISBN (Print)9783030505158
StatePublished - 1 Jan 2020
Externally publishedYes
Event17th International Conference on Image Analysis and Recognition, ICIAR 2020 - Póvoa de Varzim, Portugal
Duration: 24 Jun 202026 Jun 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12132 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th International Conference on Image Analysis and Recognition, ICIAR 2020
CityPóvoa de Varzim

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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