UniToChest: A Lung Image Dataset for Segmentation of Cancerous Nodules on CT Scans

Hafiza Ayesha Hoor Chaudhry, Riccardo Renzulli, Daniele Perlo, Francesca Santinelli, Stefano Tibaldi, Carmen Cristiano, Marco Grosso, Giorgio Limerutti, Attilio Fiandrotti*, Marco Grangetto, Paolo Fonio

*Corresponding author for this work

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

Abstract

Lung cancer has emerged as a major causes of death and early detection of lung nodules is the key towards early cancer diagnosis and treatment effectiveness assessment. Deep neural networks achieve outstanding results in tasks such as lung nodules detection, segmentation and classification, however their performance depends on the quality of the training images and on the training procedure. This paper introduces UniToChest, a dataset consisting Computed Tomography (CT) scans of 623 patients. Then, we propose a lung nodules segmentation scheme relying on a convolutional neural architecture that we also re-purpose for a nodule detection task. The experimental results show accurate segmentation of lung nodules across a wide diameter range and better detection accuracy over a traditional detection approach. The datasets and the code used in this paper are publicly made available as a baseline reference.

Original languageEnglish
Title of host publicationImage Analysis and Processing – ICIAP 2022 - 21st International Conference, 2022, Proceedings
EditorsStan Sclaroff, Cosimo Distante, Marco Leo, Giovanni M. Farinella, Federico Tombari
PublisherSpringer Science and Business Media Deutschland GmbH
Pages185-196
Number of pages12
ISBN (Print)9783031064265
DOIs
Publication statusPublished - 2022
Externally publishedYes
Event21st International Conference on Image Analysis and Processing, ICIAP 2022 - Lecce, Italy
Duration: 23 May 202227 May 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13231 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Image Analysis and Processing, ICIAP 2022
Country/TerritoryItaly
CityLecce
Period23/05/2227/05/22

Keywords

  • Chest CT scan
  • Dataset
  • Deep learning
  • DeepHealth
  • Lung nodules
  • Medical image segmentation
  • U-Net

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