Journal of Imaging Informatics in Medicine

Overview

Journal of Imaging Informatics in Medicine is a scientific journal, published by Springer Nature since 2024 in English. The journal's country of origin is Switzerland and its primary focus area is radiology.

Details

Abbr. J Imaging Inform Med

Publisher Springer Nature

Start 2024

End Continuing

p-ISSN 2948-2925

e-ISSN 2948-2933

Country Switzerland

Language English

Specialty Radiology

Recent Articles

AI-Based 3D Liver Segmentation and Volumetric Analysis in Living Donor Data

Mun S, Choi S, Kim Y, Kim K, Lee W

J Imaging Inform Med . 2025 Mar; PMID: 40087225

This study investigated the application of deep learning for 3-dimensional (3D) liver segmentation and volumetric analysis in living donor liver transplantation. Using abdominal computed tomography data from 55 donors, this...

A Two-Stage Lightweight Deep Learning Framework for Mass Detection and Segmentation in Mammograms Using YOLOv5 and Depthwise SegNet

Manolakis D, Bizopoulos P, Lalas A, Votis K

J Imaging Inform Med . 2025 Mar; PMID: 40087224

Ensuring strict medical data privacy standards while delivering efficient and accurate breast cancer segmentation is a critical challenge. This paper addresses this challenge by proposing a lightweight solution capable of...

Radiomics with Ultrasound Radiofrequency Data for Improving Evaluation of Duchenne Muscular Dystrophy

Yan D, Li Q, Chuang Y, Lin C, Shieh J, Weng W, et al.

J Imaging Inform Med . 2025 Mar; PMID: 40087223

Duchenne muscular dystrophy (DMD) is a rare and severe genetic neuromuscular disease, characterized by rapid progression and high mortality, highlighting the need for accurate ambulatory function assessment tools. Ultrasound imaging...

Facilitating Radiograph Interpretation: Refined Generative Models for Precise Bone Suppression in Chest X-rays

Ibrahim S, Selim S, Elattar M

J Imaging Inform Med . 2025 Mar; PMID: 40082331

Chest X-ray (CXR) is crucial for diagnosing lung diseases, especially lung nodules. Recent studies indicate that bones, such as ribs and clavicles, obscure 82 to 95% of undiagnosed lung cancers....

A Thyroid Nodule Ultrasound Image Grading Model Integrating Medical Prior Knowledge

Chen H, Liu C, Cheng X, Jiang C, Wang Y

J Imaging Inform Med . 2025 Mar; PMID: 40064758

In recent years, there has been increasing research on computer-aided diagnosis (CAD) using deep learning and image processing techniques. Still, most studies have focused on the benign-malignant classification of nodules....

Robust Automatic Grading of Blunt Liver Trauma in Contrast-Enhanced Ultrasound Using Label-Noise-Resistant Models

Zhang T, Li R, Zhong Z, Zhang X, Liu T, Zhou G, et al.

J Imaging Inform Med . 2025 Mar; PMID: 40063174

Recently, contrast-enhanced ultrasound (CEUS) has presented a potential value in the diagnosis of liver trauma, the leading cause of death in blunt abdominal trauma. However, the inherent speckle noise and...

I-BrainNet: Deep Learning and Internet of Things (DL/IoT)-Based Framework for the Classification of Brain Tumor

Ibrahim A, Engo G, Ame I, Nwekwo C, Al-Turjman F

J Imaging Inform Med . 2025 Mar; PMID: 40063173

Brain tumor is categorized as one of the most fatal form of cancer due to its location and difficulty in terms of diagnostics. Medical expert relies on two key approaches...

SADiff: A Sinogram-Aware Diffusion Model for Low-Dose CT Image Denoising

Niknejad Mazandarani F, Babyn P, Alirezaie J

J Imaging Inform Med . 2025 Mar; PMID: 40063172

CT image denoising is a crucial task in medical imaging systems, aimed at enhancing the quality of acquired visual signals. The emergence of diffusion models in machine learning has revolutionized...

Subtraction of Temporally Sequential Digital Mammograms: Prediction and Localization of Near-Term Breast Cancer Occurrence

Loizidou K, Skouroumouni G, Savvidou G, Constantinidou A, Vlachou E, Yiallourou A, et al.

J Imaging Inform Med . 2025 Mar; PMID: 40055291

The objective is to predict a possible near-term occurrence of a breast mass after two consecutive screening rounds with normal mammograms. For the purposes of this study, conducted between 2020...

10.

Landscape of 2D Deep Learning Segmentation Networks Applied to CT Scan from Lung Cancer Patients: A Systematic Review

Mehrnia S, Safahi Z, Mousavi A, Panahandeh F, Farmani A, Yuan R, et al.

J Imaging Inform Med . 2025 Mar; PMID: 40038137

Background: The increasing rates of lung cancer emphasize the need for early detection through computed tomography (CT) scans, enhanced by deep learning (DL) to improve diagnosis, treatment, and patient survival....