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SmartMammaCAD

Intelligent Automated System for detecting Diagnostically Challenging Breast Cancers

Total Cost €

EC-Contrib. €

Partnership

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Outcomes and
results

SmartMammaCAD project word cloud

Explore the words cloud of the SmartMammaCAD project. It provides you a very rough idea of what is the project "SmartMammaCAD" about.

magnetic registration contrast interdisciplinary cad cancerrelated illan supports imaging compensation sensitivity potentially lower tumours definitely variations dynamic software motion mri accuracy spatial transfer radiologist society algorithms dr union exhibit enhancement components diagnosis segmentation health image diseases ignacio quantify appearance area rigid goals efficiency specificity overarching benign cancer research presented radiological alvarez resonance incorporate flow kinetic descriptors critical aided breast interfaces alternative malignant differences 2020 heterogeneous vision strategic dce techniques automated proposes validate computer morphological lesions basic diagnostic temporal enhanced mass

Project "SmartMammaCAD" data sheet

The following table provides information about the project.

Coordinator	UNIVERSIDAD DE GRANADA Organization address address: CUESTA DEL HOSPICIO SN city: GRANADA postcode: 18071 website: www.ugr.es contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.
Coordinator Country	Spain [ES]
Project website	https://www.researchgate.net/project/Intelligent-Automated-System-for-Detecting-Diagnostically-Challenging-Breast-Cancers
Total cost	257˙191 €
EC max contribution	257˙191 € (100%)
Programme	1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
Code Call	H2020-MSCA-IF-2014
Funding Scheme	MSCA-IF-GF
Starting year	2015
Duration (year-month-day)	from 2015-09-01 to 2018-08-31

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	UNIVERSIDAD DE GRANADA UNIVERSIDAD DE GRANADA Organization address address: CUESTA DEL HOSPICIO SN city: GRANADA postcode: 18071 website: www.ugr.es contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	ES (GRANADA)	coordinator	257˙191.00
2	Florida State University Florida State University Organization address address: South Copeland 222 city: Tallahassee postcode: 32306 website: n.a. contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	US (Tallahassee)	partner	0.00

Map

Project objective

In this project, Dr. Ignacio Alvarez Illan proposes to develop a novel automated diagnosis system that supports the radiologist in the breast cancer diagnosis in Dynamic Contrast Enhance-Magnetic Resonance Imaging (DCE-MRI) by including critical components of the radiological work-flow such as motion compensation, segmentation and diagnosis of breast tumours. The expected results of this interdisciplinary project will definitely have applications and impact in the European society and its health and the overarching goals of the '2020 Vision for the European Research Area’. Specifically, improving diagnosis of major diseases such as breast cancer is a research priority in the European Union.

The main goal and overall objective of this project is to develop computer aided diagnosis (CAD) methods, and image processing techniques to improve diagnostic accuracy and efficiency of cancerrelated breast lesions. Non-mass-enhancing lesions exhibit a heterogeneous appearance in breast MRI with high variations in kinetic characteristics and typical morphological parameters, and have a specificity and sensitivity much lower than mass-enhancing lesions. For this reason, new segmentation algorithms and kinetic parameters can be potentially used as an alternative to the methods for mass-enhanced lesions.

To develop and implement CAD methods and image processing techniques, three different research objectives are presented in this project. They include basic research, strategic research, applied research and transfer of knowledge: i) Develop non-rigid registration and segmentation techniques to incorporate spatial variations in temporal enhancement. ii) Develop kinetic feature descriptors to quantify significant differences between the benign and malignant lesions. iii) Develop and validate algorithms, interfaces and software implementation for real applications of CAD of breast cancer.

Publications

List of publications.
year	authors and title	journal	last update
2018	Ignacio Alvarez Illan, Javier Ramirez, J. M. Gorriz, Maria Adele Marino, Daly Avendano, Thomas Helbich, Pascal Baltzer, Katja Pinker, Anke Meyer-Baese Automated Detection and Segmentation of Nonmass-Enhancing Breast Tumors with Dynamic Contrast-Enhanced Magnetic Resonance Imaging published pages: 1-11, ISSN: 1555-4309, DOI: 10.1155/2018/5308517	Contrast Media & Molecular Imaging 2018	2019-07-23
2017	J. M. Gorriz, J. Ramirez, J. Suckling, Ignacio Alvarez Illan, Andres Ortiz, F. J. Martinez-Murcia, Fermin Segovia, D. Salas-Gonzalez, Shuihua Wang Case-Based Statistical Learning: A Non-Parametric Implementation With a Conditional-Error Rate SVM published pages: 11468-11478, ISSN: 2169-3536, DOI: 10.1109/ACCESS.2017.2714579	IEEE Access 5	2019-07-23
2017	I. Alvarez Illan, A. Meyer-Baese, J. Perez Matos, M. B. I. Lobbes, K. Pinker Machine learning for challenging tumour detection and classification in breast cancer published pages: , ISSN: , DOI: 10.1594/ecr2017/C-3151	epos	2019-07-23
2017	Juan M. Gorriz, Javier Ramirez, John Suckling, F.J. Martinez-Murcia, I.A. IllÃ¡n, F. Segovia, A. Ortiz, D. Salas-GonzÃ¡lez, D. Castillo-BarnÃ©s, C.G. Puntonet A semi-supervised learning approach for model selection based on class-hypothesis testing published pages: 40-49, ISSN: 0957-4174, DOI: 10.1016/j.eswa.2017.08.006	Expert Systems with Applications 90	2019-07-23

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The information about "SMARTMAMMACAD" are provided by the European Opendata Portal: CORDIS opendata.