AIRCAD 2023 : International Workshop on Artificial Intelligence and Radiomics in Computer-Aided Diagnosis

CALL FOR PAPERS - AIRCAD2023



2nd International Workshop on Artificial Intelligence and Radiomics in Computer-Aided Diagnosis AIRCAD2023

held in conjunction with the 22nd International Conference on Image Analysis and Processing ICIAP2023,

Udine, Italy, 11-15th Sep 2023



https://sites.google.com/view/aircad2023



AIMS AND SCOPE

Nowadays, healthcare systems collect and provide most medical data in digital form. The availability of medical data enables a large number of artificial intelligence applications, and there is a growing interest in the quantitative analysis of clinical images using techniques such as Positron Emission Tomography, Computerized Tomography, and Magnetic Resonance Imaging, mainly applied to texture analysis and radiomics. In particular, thanks to machine and deep learning, researchers can generate insights to improve the discovery of new therapeutic tools, support diagnostic decisions, aid in the rehabilitation process, etc. However, the increasing amount of available data may lead to a more significant effort to make a diagnosis. Moreover, this task is even more challenging due to the high inter/intra patient variability, the availability of various imaging techniques, and the need to consider data from multiple sensors and sources, which brought to the well-known domain shift issue.



To address the problems described, radiologists and pathologists today use tools to assist them in analysing biomedical images. They are known as Computer-Aided Diagnosis (CAD) systems and they allow to mitigate or eliminate the difficulties due to inter- and intra-observer variability, represented by various assessments of the same region, under the same assumptions, by the same physician at different times, and various assessments of the same region by several physicians, thanks to appropriate algorithms. Further relevant issues are data access, which may be delayed or even prevented for various reasons, such as privacy, security, intellectual property, and representativeness of the captured sample compared to the real population. For these reasons, researchers have recently explored the use of synthetic data, both for training the models and to estimate and teach systems in situations that have not been observed in actual reality.



This workshop aims to provide an overview of recent advances in the field of biomedical image processing using machine learning, deep learning, artificial intelligence, and radiomics features, placing particular attention on contributions dealing with practical applications, for example, potential alternative solution against domain shift, or exploiting synthetic images to teach actual CAD systems. In particular, the ultimate goal is to analyse how these techniques can be employed in the typical medical image processing workflow, from image acquisition to classification, including retrieval, disease detection, prediction, and classification.



TOPICS

The workshop calls for submissions addressing, but not limited to, the following topics:

- Biomedical Image Processing

- Machine and Deep Learning techniques for image analysis (i.e., segmentation of cells, tissues, organs, lesions; classification of cells, diseases, tumours, etc.)

- Image Registration Techniques

- Image Preprocessing Techniques

- Image-based 3D reconstruction

- Computer-Aided Detection and Diagnosis Systems (CADs)

- Biomedical Image Analysis

- Radiomics and Artificial intelligence for personalised medicine

- Machine and Deep Learning as tools to support medical diagnoses and decisions

- Image retrieval (e.g., context-based retrieval, lesion similarity)

- CAD architectures

- Advanced architecture for biomedical image remote processing, elaboration, and transmission

- 3D Vision, Virtual, Augmented, and Mixed Reality applications for remote surgery

- Image processing techniques for privacy-preserving AI in medicine.



SUBMISSION GUIDELINES

Accepted papers will be included in the ICIAP 2023 proceedings, which will be published by Springer as Lecture Notes in Computer Science series (LNCS). When preparing your contribution, please follow the guidelines provided by Springer. The maximum number of pages is 12 pages including references. Each contribution will be reviewed based on originality, significance, clarity, soundness, relevance and technical content.



The submission will be handled electronically via a unique Conference's CMT Website for all the workshops belonging to the ICIAP Medical Imaging Hub:

https://cmt3.research.microsoft.com/ICIAPMIH2023/

During the submission, you must select the correct Track, which is Artificial Intelligence and Radiomics in Computer-Aided Diagnosis (AIRCAD).



Once accepted, the presence of at least one author at the event and the oral presentation of the paper are expected. There are two registration modalities:

- Workshops/Tutorials pass, which covers only tutorials and workshops (2 days)

- Conference pass, which includes the main conference, workshops/tutorials, and social events (5 days).

For more details about the registration, see the ICIAP main conference website.



IMPORTANT DATES

- Paper Submission: June 30th, 2023

- Notifications to Authors: July 30th, 2023

- Camera Ready Papers Due: August 15th, 2023

- Workshop Event: September 11th, 2023



ORGANIZERS

Albert Comelli, Ri.MED Foundation, [email protected]

Cecilia Di Ruberto, University of Cagliari, [email protected]

Andrea Loddo, University of Cagliari, [email protected]

Lorenzo Putzu, University of Cagliari, [email protected]

Alessandro Stefano, Institute of Molecular Bioimaging and Physiology, National Research Council of Cefalu’, [email protected]



TECHNICAL PROGRAM COMMITTEE (CONFIRMED)

Seyed-Ahmad Ahmadi, NVIDIA (Germany), [email protected]
Monica Bianchini, University of Siena (Italy), [email protected]
Mario D'Acunto, National Research Council (Italy), [email protected]
Navdeep Dahiya, Georgia Institute of Technology (USA), [email protected]
Angelo Genovese, University of Milano (Italy), [email protected]
Jon Ander Gómez Adrián, Universitat Politècnica de València (Spain), [email protected]
Marco Grangetto, University of Torino (Italy), [email protected]
Mario Molinara, University of Cassino and Southern Lazio (Italy), [email protected]
Davide Moroni, National Research Council (Italy), [email protected]
Paolo Napoletano, University of Milan, Bicocca (Italy), [email protected]
Antonio Parziale, University of Salerno (Italy), [email protected]
Giovanni Pasini, Sapienza, University of Rome (Italy), [email protected]
Luca Pireddu, CRS4 (Italy), [email protected]
Vincenzo Piuri, University of Milan (Italy), [email protected]
Mubashara Rehman, University of Udine (Italy), [email protected]
Giorgio Russo, IBFM-CNR (Italy), [email protected]
Mattia Savardi, University of Brescia (Italy), [email protected]
Alberto Signoroni, University of Brescia (Italy), [email protected]
Nicola Strisciuglio, University of Twente (Netherlands), [email protected]
Enzo Tartaglione, Télécom Paris, Institut Polytechnique de Paris (France), [email protected]
Francesco Tortorella, University of Salerno (Italy), [email protected]
Lorenzo Ugga, University of Naples Federico II (Italy), [email protected]
Federica Vernuccio, University of Padova (Italy), [email protected]