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


When Sep 11, 2023 - Sep 15, 2023
Where Udine
Submission Deadline Jul 15, 2023
Notification Due Jul 30, 2023
Final Version Due Aug 15, 2023
Categories    image processing   computer vision   medical imaging   radiomics

Call For Papers


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


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.


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.


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:

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.


- Paper Submission: June 30th, 2023

- Notifications to Authors: July 30th, 2023

- Camera Ready Papers Due: August 15th, 2023

- Workshop Event: September 11th, 2023


Albert Comelli, Ri.MED Foundation,

Cecilia Di Ruberto, University of Cagliari,

Andrea Loddo, University of Cagliari,

Lorenzo Putzu, University of Cagliari,

Alessandro Stefano, Institute of Molecular Bioimaging and Physiology, National Research Council of Cefalu’,


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

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