MLCN 2022 special issue

We are delighted to formally announce the inaugural Special Issue of the Machine Learning in Clinical Neuroimaging (MLCN) journal, dedicated to showcasing a curated selection of papers originating from the 5th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2022). This workshop took place on September 18, 2022, as a satellite event in conjunction with the 25th International Conference on Medical Imaging Computing and Computer Assisted Intervention (MICCAI 2022) in Singapore. This event serves as an integral platform for fostering continued, annual discourse among luminaries in the fields of machine learning and clinical neuroimaging.

The solicitation for papers for this Special Issue commenced on May 2, 2022, and subsequently concluded on July 8, 2022. Each manuscript submitted underwent a meticulous evaluation process, featuring a double-blind review conducted by a panel of three or more esteemed Program Committee members. We are pleased to announce the inclusion of 17 papers in the official workshop proceedings, accessible at the following link:

Among these, a discerning subset of seven papers was extended an invitation to submit an augmented version for consideration in this Special Issue. This invitation was developed based on a comprehensive assessment of the original submissions, coupled with a thorough examination of the feedback from the Associate Editors, reviewers, and the authors' responses. Subsequently, the received submission underwent a rigorous review process. We are pleased to confirm the acceptance of this submission for inclusion in this Special Issue. The accepted paper, entitled "Weakly Supervised Intracranial Hemorrhage Segmentation using Head-Wise Gradient-Infused Self-Attention Maps from a Swin Transformer in Categorical Learning," has undergone rigorous evaluation and met the high standards set by the MELBA journal.

We extend our sincere appreciation to all contributors, reviewers, and members of the Program Committee for their invaluable contributions, which have collectively culminated in the successful realization of this Special Issue. We are confident that this publication will significantly contribute to the burgeoning intersection of machine learning and clinical neuroimaging.

The guest editors,
  • Seyed Mostafa Kia;
  • Mohamad Habes.

1 paper