Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

The autoPET challenge: Towards fully automated lesion segmentation in oncologic PET/CT imaging
Sergios Gatidis, Marcel Früh, Matthias P. Fabritius, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

TMTV-Net: fully automated total metabolic tumor volume segmentation in lymphoma PET/CT images — a multi-center generalizability analysis
Fereshteh Yousefirizi, Ivan S. Klyuzhin, Joo Hyun O, et al.
European Journal of Nuclear Medicine and Molecular Imaging (2024) Vol. 51, Iss. 7, pp. 1937-1954
Closed Access | Times Cited: 18
A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond
Junyu Chen, Yihao Liu, Shuwen Wei, et al.
Medical Image Analysis (2024) Vol. 100, pp. 103385-103385
Open Access | Times Cited: 16
Deep Semisupervised Transfer Learning for Fully Automated Whole-Body Tumor Quantification and Prognosis of Cancer on PET/CT
Kevin Leung, Steven P. Rowe, Moe S. Sadaghiani, et al.
Journal of Nuclear Medicine (2024) Vol. 65, Iss. 4, pp. 643-650
Open Access | Times Cited: 12
Multi-modal medical Transformers: A meta-analysis for medical image segmentation in oncology
Gustavo Andrade-Miranda, Vincent Jaouen, Olena Tankyevych, et al.
Computerized Medical Imaging and Graphics (2023) Vol. 110, pp. 102308-102308
Closed Access | Times Cited: 20
Filters, Thresholds, and Geodesic Distances for Scribble-Based Interactive Segmentation of Medical Images
Zdravko Marinov, Alexander Jaus, Jens Kleesiek, et al.
Lecture notes in computer science (2025), pp. 39-56
Closed Access
Taking a Step Back: Revisiting Classical Approaches for Efficient Interactive Segmentation of Medical Images
Zdravko Marinov, Alexander Jaus, Jens Kleesiek, et al.
Lecture notes in computer science (2025), pp. 101-125
Closed Access
Development and validation of pan-cancer lesion segmentation AI-model for whole-body 18F-FDG PET/CT in diverse clinical cohorts
Fahmida Haque, Alex Chen, Nathan Lay, et al.
Computers in Biology and Medicine (2025) Vol. 190, pp. 110052-110052
Closed Access
Sliding Window Fastedit: A Framework for Lesion Annotation in Whole-Body Pet Images
Matthias Hadlich, Zdravko Marinov, Moon Kim, et al.
(2024), pp. 1-5
Open Access | Times Cited: 2
Semi-supervised learning towards automated segmentation of PET images with limited annotations: application to lymphoma patients
Fereshteh Yousefirizi, Isaac Shiri, Joo Hyun O, et al.
Physical and Engineering Sciences in Medicine (2024) Vol. 47, Iss. 3, pp. 833-849
Closed Access | Times Cited: 1
Advancing Multi-organ and Pan-Cancer Segmentation in Abdominal CT Scans Through Scale-Aware and Self-attentive Modulation
Pengju Lyu, Junchen Xiong, Wei Fang, et al.
Lecture notes in computer science (2024), pp. 84-101
Closed Access | Times Cited: 1
A Semi-supervised Abdominal Multi-organ Pan-Cancer Segmentation Framework with Knowledge Distillation and Multi-label Fusion
Zeng-Min Zhang, Xiaomeng Duan, Yanjun Peng, et al.
Lecture notes in computer science (2024), pp. 346-361
Closed Access
From Whole-Body to Abdomen: Streamlined Segmentation of Organs and Tumors via Semi-Supervised Learning and Efficient Coarse-to-Fine Inference
Shoujin Huang, Huaishui Yang, Lifeng Mei, et al.
Lecture notes in computer science (2024), pp. 283-292
Closed Access
Multi-task Learning with Iterative Training in Hybrid Labeling Dataset for Semi-supervised Abdominal Multi-organ and Tumor Segmentation
Zhiqiang Zhong, Rongxuan He, Deming Zhu, et al.
Lecture notes in computer science (2024), pp. 306-318
Closed Access
Selected Partially Labeled Learning for Abdominal Organ and Pan-Cancer Segmentation
Yuntao Zhu, Liwen Zou, Linyao Li, et al.
Lecture notes in computer science (2024), pp. 209-221
Closed Access
Attention Mechanism-Based Deep Supervision Network for Abdominal Multi-organ Segmentation
Peng An, Yurou Xu, Panpan Wu
Lecture notes in computer science (2024), pp. 319-332
Closed Access
Partial-Labeled Abdominal Organ and Cancer Segmentation via Cascaded Dual-Decoding U-Net
Zhiyu Ye, Hairong Zheng, Tong Zhang
Lecture notes in computer science (2024), pp. 236-252
Closed Access
Multi-Organ and Pan-Cancer Segmentation Framework from Partially Labeled Abdominal CT Datasets: Fine and Swift nnU-Nets with Label Fusion
Y. Kong, Kwangtai Kim, Seoi Jeong, et al.
Lecture notes in computer science (2024), pp. 267-282
Closed Access
Conformer: A Parallel Segmentation Network Combining Swin Transformer and Convolutional Neutral Network
Yanbin Chen, Zhicheng Wu, Hao Chen, et al.
Lecture notes in computer science (2024), pp. 253-266
Closed Access
Abdomen Multi-organ Segmentation Using Pseudo Labels and Two-Stage
Xinye Yang, Xuru Zhang, Xiaochao Yan, et al.
Lecture notes in computer science (2024), pp. 41-53
Closed Access
2.5D U-Net for Abdominal Multi-organ Segmentation
Ruixiang Lei, Mingjing Yang
Lecture notes in computer science (2024), pp. 76-83
Closed Access
Context-Aware Cutmix is All You Need for Universal Organ and Cancer Segmentation
Qin Zhou, Peng Liu, Guoyan Zheng
Lecture notes in computer science (2024), pp. 28-40
Closed Access
Exploiting Pseudo-labeling and nnU-Netv2 Inference Acceleration for Abdominal Multi-organ and Pan-Cancer Segmentation
Ziyan Huang, Ye Jin, Haoyu Wang, et al.
Lecture notes in computer science (2024), pp. 15-27
Closed Access
A Two-Step Deep Learning Approach for Abdominal Organ Segmentation
Jianwei Gao, Juan Xu, Honggao Fei, et al.
Lecture notes in computer science (2024), pp. 54-62
Closed Access
Semi-supervised Two-Stage Abdominal Organ and Tumor Segmentation Model with Pseudo-labeling
Li Mao
Lecture notes in computer science (2024), pp. 63-75
Closed Access
3D Swin Transformer for Partial Medical Auto Segmentation
Aneesh Rangnekar, Jue Jiang, Harini Veeraraghavan
Lecture notes in computer science (2024), pp. 222-235
Closed Access
Page 1 - Next Page

Scroll to top