Medical Image Analysis: New Opportunities and Challenges

A special issue of Journal of Imaging (ISSN 2313-433X). This special issue belongs to the section "Medical Imaging".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 49

Special Issue Editor


E-Mail Website
Guest Editor
Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104-4283, USA
Interests: medical image analysis; deep learning; diffusion imaging; traumatic brain injury

Special Issue Information

Dear Colleagues,

The development of reliable artificial intelligence tools for medical image analysis is often constrained by the limited availability of high-quality, annotated datasets. This scarcity of data spans multiple domains, from prenatal and fetal imaging to traumatic brain injury and neurodegenerative disease, where acquiring standardized, multimodal datasets remains a major challenge. This Special Issue will bring together innovative approaches addressing data scarcity and heterogeneity through synthetic data generation, cross-modality harmonization, and domain-adaptive deep learning.

Particular attention will be paid to methods that combine high-resolution microscopy, histological imaging, and MRI to link microscopic and macroscopic scales, as well as studies that use synthetic or self-supervised learning to augment limited datasets. Cross-species frameworks such as porcine or rodent imaging that inform human neuroanatomy are also encouraged. Our overarching goal is to highlight computational strategies that expand the effective data landscape, leading to more generalizable, interpretable, and biologically grounded models for clinical imaging.

Dr. Javid Dadashkarimi
Guest Editor

Manuscript Submission Information

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Keywords

  • synthetic data
  • data scarcity
  • histology
  • high-resolution microscopy
  • deep learning
  • domain adaptation
  • multimodal fusion
  • prenatal imaging
  • neurodegeneration
  • cross-species modeling

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Published Papers

This special issue is now open for submission.
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