Special Issue on Open the Brain: horizons and challenges in brain image analysis Submission Date: 2025-05-20 The rapid advancement of Artificial Intelligence (AI) is profoundly impacting healthcare, particularly in brain-focused medical imaging. AI- based tools are revolutionizing diagnostics by improving speed, reducing costs, and enhancing accuracy.

Brain research through image analysis is a standout area, enabling preventive diagnoses, predicting disease progression, assisting in surgeries, and facilitating non-invasive therapy studies. These advancements are transforming the field and drawing interest from technical experts and industry stakeholders.

Despite significant progress, brain imaging faces challenges such as data scarcity, lack of standardization in image acquisition, labeling issues, and other technical hurdles. The brain's complexity and neurological diseases add further difficulties. AI is addressing these challenges by enhancing data analysis, improving imaging techniques, and offering robust predictive models, driving major advancements in brain research.

This special issue aims to explore critical aspects, innovative solutions, and prospects in brain-focused medical imaging. We aim to demonstrate how AI can overcome existing challenges and unlock new possibilities in diagnosing and treating neurological conditions. The issue will highlight cutting-edge research, discuss ethical and practical considerations of AI in healthcare, and provide a comprehensive overview of the current state and future directions of AI-driven brain imaging. Building on the recent ICPR 2024 challenge (https://iplab.dmi.unict.it/mfs/ms-les-seg/), this Special Issue invites numerous submissions in the related field, extending a special invitation to the top participants from the challenge.

Topics of interest

Machine Learning and Deep Learning Algorithms for Brain Image Analysis

Pattern Recognition for Early Diagnosis of Neurological Diseases

Automated Brain Image Segmentation Techniques

Enhancing Brain Image Quality and Artifact Detection

Generative Models for Brain Image Synthesis and Augmentation

Foundation Models in Brain Image Analysis

Multimodal Data Integration for Brain Pattern Recognition

Predictive Models for Neurological Disease Progression

Ethical Considerations and Responsible Development of AI Systems for Brain Imaging

Guest editors:

Sebastiano Battiato, PhD

University of Catania, Catania, Italy

(sebastiano.battiato@unict.it)

Francesco Guarnera, PhD

University of Catania, Catania, Italy

(francesco.guarnera@unict.it)

Alessia Rondinella, PhD

University Campus Bio-Medico of Rome, Rome, Italy

(alessia.rondinella@unicampus.it)

Alessandro Ortis, PhD

University of Catania, Catania, Italy

(alessandro.ortis@unict.it)

Daniele Ravì, PhD

University College London, London, UK

(d.ravi@ucl.ac.uk)

Manuscript submission information:

The PRL's submission system (Editorial Manager®) will be open for submissions to our Special Issue from May 1st, 2025. When submitting your manuscript please select the article type VSI: HCBIA. Both the Guide for Authors and the submission portal could be found on the Journal Homepage: Guide for authors - Pattern Recognition Letters - ISSN 0167-8655 | ScienceDirect.com by Elsevier.

Important dates

Submission Portal Open: May 1st, 2025

Submission Deadline: May 20th, 2025

Acceptance Deadline: September 30th, 2025

Keywords:

brain image analysis, medical imagina, medical generative data, neurological disease, multimodal data