A Tumour and Liver Automatic Segmentation (ATLAS) Dataset on Contrast-Enhanced Magnetic Resonance Imaging for Hepatocellular Carcinoma

Author:

Quinton Félix1ORCID,Popoff Romain123,Presles Benoît1,Leclerc Sarah1ORCID,Meriaudeau Fabrice1,Nodari Guillaume2,Lopez Olivier2,Pellegrinelli Julie23ORCID,Chevallier Olivier4ORCID,Ginhac Dominique5ORCID,Vrigneaud Jean-Marc12ORCID,Alberini Jean-Louis124

Affiliation:

1. Institut de Chimie Moléculaire de l’Université de Bourgogne, ICMUB UMR CNRS 6302, Université Bourgogne Franche-Comté, 21000 Dijon, France

2. Service de Médecine Nucléaire, Centre Georges-François Leclerc, 21000 Dijon, France

3. Service de Radiologie, Centre Georges-François Leclerc, 21000 Dijon, France

4. Service de Radiologie et Imagerie Medicale Diagnostique et Therapeutique, Centre Hospitalier Universitaire, 21000 Dijon, France

5. Laboratoire Imagerie et Vision Artificielle (ImViA), Universite de Bourgogne Franche-Comté, 21000 Dijon, France

Abstract

Liver cancer is the sixth most common cancer in the world and the fourth leading cause of cancer mortality. In unresectable liver cancers, especially hepatocellular carcinoma (HCC), transarterial radioembolisation (TARE) can be considered for treatment. TARE treatment involves a contrast-enhanced magnetic resonance imaging (CE-MRI) exam performed beforehand to delineate the liver and tumour(s) in order to perform dosimetry calculation. Due to the significant amount of time and expertise required to perform the delineation process, there is a strong need for automation. Unfortunately, the lack of publicly available CE-MRI datasets with liver tumour annotations has hindered the development of fully automatic solutions for liver and tumour segmentation. The “Tumour and Liver Automatic Segmentation” (ATLAS) dataset that we present consists of 90 liver-focused CE-MRI covering the entire liver of 90 patients with unresectable HCC, along with 90 liver and liver tumour segmentation masks. To the best of our knowledge, the ATLAS dataset is the first public dataset providing CE-MRI of HCC with annotations. The public availability of this dataset should greatly facilitate the development of automated tools designed to optimise the delineation process, which is essential for treatment planning in liver cancer patients.

Funder

Agence Nationale de la Recherche

Publisher

MDPI AG

Subject

Information Systems and Management,Computer Science Applications,Information Systems

Reference25 articles.

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2. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries;Bray;CA Cancer J. Clin.,2018

3. Loco-regional treatment of HCC: Current status;Crocetti;Clin. Radiol.,2017

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