title: A computational framework for cancer response assessment based on oncological PET-CT scans.
abstract: In this work we present a comprehensive computational framework to help in the clinical assessment of cancer response from a pair of time consecutive oncological PET-CT scans. In this scenario, the design and implementation of a supervised machine learning system to predict and quantify cancer progression or response conditions by introducing a novel feature set that models the underlying clinical context is described. Performance results in 100 clinical cases (corresponding to 200 whole body PET-CT scans) in comparing expert-based visual analysis and classifier decision making show up to 70% accuracy within a completely automatic pipeline and 90% accuracy when providing the system with expert-guided PET tumor segmentation masks.
authors.affiliation: Autonomous University of Barcelona, Faculty of Medicine, 08193 Barcelona, Spain. Electronic address: fredsampedro@gmail.com.
authors.forename: Frederic
authors.initials: F
authors.lastname: Sampedro
authors.affiliation: Computer Vision Center, Campus UAB, Edifici O, 08193, Bellaterra, Barcelona, Spain. Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Gran Via de les Corts 585, 08007, Barcelona, Spain. Electronic address: sergio@maia.ub.es.
authors.forename: Sergio
authors.initials: S
authors.lastname: Escalera
authors.affiliation: Hospital de Sant Pau, Nuclear Medicine Department, 89 Carrer Sant Quintí, 08026 Barcelona, Spain. Electronic address: adomenech@santpau.cat.
authors.forename: Anna
authors.initials: A
authors.lastname: Domenech
authors.affiliation: Hospital de Sant Pau, Nuclear Medicine Department, 89 Carrer Sant Quintí, 08026 Barcelona, Spain.
authors.forename: Ignasi
authors.initials: I
authors.lastname: Carrio
mesh_terms: D001185:Artificial Intelligence; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009369:Neoplasms / Q000000981:diagnostic imaging*; D049268:Positron-Emission Tomography / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*; D051598:Whole Body Imaging
keywords: Computer aided diagnosis; Image processing; Machine learning; Nuclear medicine; Quantitative analysis