Impact Factor
3.90
Journal Citation Impact
Estimated influence, citation density, publishing volume, and citation integrity from the analytics table.
Citation rate
4.12
1,886 total citations
h5-index
43
h5 depth signal
Cited share
83.1%
404 of 486
Total citations
1,886
Citation footprint
Metric signal
3.52
External metric anchor
Self-citation
5.2%
99 self-citations
Citations Trend
Monthly Publications Cadence
Citing Geographic Demographics
Germany
584
United States
437
China
384
Japan
250
Canada
233
Citing Fields of Research
Computer Vision & Graphics
604
AI & Machine Learning
542
Robotics
541
Brain Imaging
322
Abdominal Surgery
291
Publishing Activity & Reach
Volume, recency, access pattern, and citing-community signals from the journal analytics record.
All-time article footprint
3,772
Articles tracked across the journal lifetime
Indexed publication set
486
404 cited publications
Last 12 months
277
23.1 publications/month
Open access share
56.3%
156 OA publications in the last year
Leading citing country
Germany
584 citing publications
Leading citing field
Computer Vision & Graphics
604 citing publications
Latest tracked publication
17 October 2026
10 recent records available
Coverage & Indexing History
v4n1, Jan. 2009-
v4n1, Jan. 2009-
Research Focus & Classification
Indexed Subjects
Robotics
Computer Vision & Graphics
AI & Machine Learning
Human-Machine Interaction
Abdominal Surgery
Patient Care
Broad Categories
General Surgery
Radiology
Robotics
Computer Vision & Graphics
Human-Machine Interaction
Musculoskeletal Disorders
Brain Imaging
Patient Care
Diagnostic & Therapeutic Ultrasound
MeSH Descriptors
Image Interpretation, Computer-Assisted
Surgery, Computer-Assisted
Latest Publications
Recent article records with DOI-first linking and condensed abstracts.
01
DOI 10.1007/s11548-026-03805-x
Open DOI
Improving the fairness and robustness of deep learning classification models through bias mitigation and post hoc calibration
Purpose:: The goal of this study was to enhance the fairness and clinical applicability of deep learning models for classifying Alzheimer’s disease from structural MRI scans. To achieve this, we addressed two key challenges: age-related ...
02
DOI 10.1007/s11548-026-03782-1
Open DOI
Learning from the unseen: synthetic data for scoliosis AI segmentation
Purpose: Severe scoliosis remains challenging for 3D vertebral segmentation because annotated pathological computed tomography (CT) data are scarce. Methods: We synthesize scoliosis-like CT volumes by jointly warping public healthy spine...
03
DOI 10.1007/s11548-026-03798-7
Open DOI
Resection zone prediction for parenchyma-sparing hepatectomy planning: a comparative study of three modeling paradigms
Purpose:: Parenchyma-sparing hepatectomy planning depends on accurate resection zones that preserve functional liver tissue without compromising oncological margins. This work investigates how different levels of anatomical and functiona...
04
DOI 10.1007/s11548-026-03791-0
Open DOI
Development of a support system for total hip arthroplasty: evaluation of lower limb loads using virtual and dummy human body models
Purpose: The direct anterior approach (DAA) is one of the procedures used for total hip arthroplasty (THA) and offers advantages such as faster postoperative recovery. A lower limb traction operating table has been developed to assist in...
05
DOI 10.1007/s11548-026-03801-1
Open DOI
Evaluation of an automated workflow for TSN-based bounded-latency communication in ISO IEEE 11073 SDC-based medical networks
Purpose: Interoperable, vendor-independent communication between medical devices in operating rooms has been enabled by the ISO IEEE 11073 Service-oriented Device Connectivity (SDC) standard since 2019. However, mechanisms for predictabl...
06
DOI 10.1007/s11548-026-03799-6
Open DOI
Assessing selective interaction for reliable and trustworthy robotic surgical assistance
07
DOI 10.1007/s11548-026-03774-1
Open DOI
Evaluation of 5G cellular and Wi-Fi 6 for cable-free surgical navigation using ISO/IEEE 11073 SDC
Purpose: As clinics strive for optimal patient safety and surgical outcomes as well as efficient and cost-effective operation, operating rooms have been investigated for workflow disruptions, risks, and inefficiencies. Notably, medical d...
08
DOI 10.1007/s11548-026-03800-2
Open DOI
Introducing FRAM as a tool for surgical process modeling: a case study for understanding surgical scheduling complexity
Introduction: Surgical processes are inherently variable leading to unexpected delays and cancellations. Due to inefficient and outdated processes, there is a need to understand and improve potential bottlenecks. However, traditional sur...
09
DOI 10.1007/s11548-026-03796-9
Open DOI
Deep learning-based segmentation of peritoneal cancer index regions from CT imaging
Purpose: Peritoneal metastases (PM) are staged using the surgically determined peritoneal cancer index (PCI), which requires invasive laparoscopic assessment. Although CT is routinely used for preoperative evaluation, imaging-based asses...
10
DOI 10.1007/s11548-026-03795-w
Open DOI
Performance changes in automated lesion detection under federated learning with sequential institution addition
Purpose: Federated learning (FL) enables multiple institutions to collaboratively train machine learning models while keeping data local and has attracted attention in medical image processing, including computer-aided detection (CAD). I...
Bibliographical & Catalog Notes
Supplments consist of the Proceedings of the ... International Congress and Exhibition.
Description based on: Vol. 4, no. 1 (Jan. 2009); title from cover.
Latest issue consulted: Vol. 4, no. 3 (May 2009).
Some vols. have suppls.
Also issued online.
Supplements contains later proceedings of: Computer assisted radiology and surgery : proceedings of the ... international congress and exhibition (DLC) 2002243534 (OCoLC)51008870 (DNLM)101157847.