You are currently viewing a new version of our website. To view the old version click .

Journal of Imaging, Volume 11, Issue 4

April 2025 - 35 articles

Cover Story: Prostate cancer (PCa) is the second most common malignancy among men worldwide; however, it is highly curable if detected early. Hence, the main clinical challenge is to accurately identify those with and without cancer as early as possible. This paper introduces a novel multi-encoder cross-attention 3D architecture for assessing PCa presence in whole bi-parametric magnetic resonance imaging (MRI) volumes. With an architecture specifically designed to exploit complementary imaging features alongside clinical variables and the ProstateNET Imaging Archive, the largest image database worldwide for PCa mpMRI data, this study establishes new baselines for performances. The proposed method paves the way towards the clinical adoption of deep learning models for accurately determining the presence of PCa in patient populations. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
  • You may sign up for email alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.

Articles (35)

  • Article
  • Open Access
2,592 Views
29 Pages

Face anti-spoofing detection is crucial for identity verification and security monitoring. However, existing single-modal models struggle with feature extraction under complex lighting conditions and background variations. Moreover, the feature distr...

  • Article
  • Open Access
2,384 Views
22 Pages

A Hybrid CNN Framework DLI-Net for Acne Detection with XAI

  • Shaila Sharmin,
  • Fahmid Al Farid,
  • Md. Jihad,
  • Shakila Rahman,
  • Jia Uddin,
  • Rayhan Kabir Rafi,
  • Radia Hossan and
  • Hezerul Abdul Karim

Acne is a prevalent skin condition that can significantly impact individuals’ psychological and physiological well-being. Detecting acne lesions is crucial for improving dermatological care and providing timely treatment. Numerous studies have...

  • Article
  • Open Access
1 Citations
1,557 Views
19 Pages

Underwater image enhancement (UIE) is inherently challenging due to complex degradation effects such as light absorption and scattering, which result in color distortion and a loss of fine details. Most existing methods focus on spatial-domain proces...

  • Article
  • Open Access
1 Citations
1,348 Views
13 Pages

This paper presents the mathematical framework of Recurrence Quantification Analysis (RQA) for dynamic video processing, exploring its applications in two primary tasks: scene change detection and adaptive foreground/background segmentation. Original...

  • Article
  • Open Access
818 Views
21 Pages

Satellite video geographic alignment can be applied to target detection and tracking, true 3D scene construction, image geometry measurement, etc., which is a necessary preprocessing step for satellite video applications. In this paper, a multi-scale...

  • Article
  • Open Access
1,560 Views
28 Pages

Does the quality that renders multi-stable images fascinating, the sudden perceptual reorganization, the switching from one interpretation into another, also make these images appear beautiful? Or is the aesthetic quality of multi-stable figures unre...

  • Review
  • Open Access
2 Citations
2,897 Views
18 Pages

Artificial Intelligence in Placental Pathology: New Diagnostic Imaging Tools in Evolution and in Perspective

  • Antonio d’Amati,
  • Giorgio Maria Baldini,
  • Tommaso Difonzo,
  • Angela Santoro,
  • Miriam Dellino,
  • Gerardo Cazzato,
  • Antonio Malvasi,
  • Antonella Vimercati,
  • Leonardo Resta and
  • Gian Franco Zannoni
  • + 1 author

Artificial intelligence (AI) has emerged as a transformative tool in placental pathology, offering novel diagnostic methods that promise to improve accuracy, reduce inter-observer variability, and positively impact pregnancy outcomes. The primary obj...

  • Article
  • Open Access
1,241 Views
16 Pages

Validation of Quantitative Ultrasound and Texture Derivative Analyses-Based Model for Upfront Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer

  • Adrian Wai Chan,
  • Lakshmanan Sannachi,
  • Daniel Moore-Palhares,
  • Archya Dasgupta,
  • Sonal Gandhi,
  • Rossanna Pezo,
  • Andrea Eisen,
  • Ellen Warner,
  • Frances C. Wright and
  • Nicole Look Hong
  • + 7 authors

This work was conducted in order to validate a pre-treatment quantitative ultrasound (QUS) and texture derivative analyses-based prediction model proposed in our previous study to identify responders and non-responders to neoadjuvant chemotherapy in...

  • Article
  • Open Access
1,206 Views
18 Pages

Transforming images from day style to night style is crucial for enhancing perception in autonomous driving and smart surveillance. However, existing CycleGAN-based approaches struggle with texture loss, structural inconsistencies, and high computati...

  • Article
  • Open Access
1 Citations
1,806 Views
22 Pages

Optimizing Digital Image Quality for Improved Skin Cancer Detection

  • Bogdan Dugonik,
  • Marjan Golob,
  • Marko Marhl and
  • Aleksandra Dugonik

The rising incidence of skin cancer, particularly melanoma, underscores the need for improved diagnostic tools in dermatology. Accurate imaging plays a crucial role in early detection, yet challenges related to color accuracy, image distortion, and r...

of 4

Get Alerted

Add your email address to receive forthcoming issues of this journal.

XFacebookLinkedIn
J. Imaging - ISSN 2313-433X