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Automated Lymph Node (LN) detection is an important clinical diagnostic task but very challenging due to the low contrast of surrounding structures in Computed Tomography (CT) and to their varying sizes, poses, shapes and sparsely…

Computer Vision and Pattern Recognition · Computer Science 2015-09-17 Holger R. Roth , Le Lu , Ari Seff , Kevin M. Cherry , Joanne Hoffman , Shijun Wang , Jiamin Liu , Evrim Turkbey , Ronald M. Summers

Finding abnormal lymph nodes in radiological images is highly important for various medical tasks such as cancer metastasis staging and radiotherapy planning. Lymph nodes (LNs) are small glands scattered throughout the body. They are…

Computer Vision and Pattern Recognition · Computer Science 2023-07-31 Ke Yan , Dakai Jin , Dazhou Guo , Minfeng Xu , Na Shen , Xian-Sheng Hua , Xianghua Ye , Le Lu

As lung cancer evolves, the presence of enlarged and potentially malignant lymph nodes must be assessed to properly estimate disease progression and select the best treatment strategy. Following the clinical guidelines, estimation of…

Image and Video Processing · Electrical Eng. & Systems 2022-05-03 David Bouget , André Pedersen , Johanna Vanel , Haakon O. Leira , Thomas Langø

Automatic lymph node (LN) segmentation and detection for cancer staging are critical. In clinical practice, computed tomography (CT) and positron emission tomography (PET) imaging detect abnormal LNs. Despite its low contrast and variety in…

Image and Video Processing · Electrical Eng. & Systems 2022-12-23 Al-Akhir Nayan , Boonserm Kijsirikul , Yuji Iwahori

Robust localization of lymph nodes (LNs) in multiparametric MRI (mpMRI) is critical for the assessment of lymphadenopathy. Radiologists routinely measure the size of LN to distinguish benign from malignant nodes, which would require…

Image and Video Processing · Electrical Eng. & Systems 2025-04-08 Tejas Sudharshan Mathai , Sungwon Lee , Thomas C. Shen , Zhiyong Lu , Ronald M. Summers

Lymph node (LN) assessment is a critical, indispensable yet very challenging task in the routine clinical workflow of radiology and oncology. Accurate LN analysis is essential for cancer diagnosis, staging, and treatment planning. Finding…

Computer Vision and Pattern Recognition · Computer Science 2025-04-24 Yirui Wang , Qinji Yu , Ke Yan , Haoshen Li , Dazhou Guo , Li Zhang , Le Lu , Na Shen , Qifeng Wang , Xiaowei Ding , Xianghua Ye , Dakai Jin

Determining the spread of GTV$_{LN}$ is essential in defining the respective resection or irradiating regions for the downstream workflows of surgical resection and radiotherapy for many cancers. Different from the more common enlarged…

Computer Vision and Pattern Recognition · Computer Science 2020-09-01 Chun-Hung Chao , Zhuotun Zhu , Dazhou Guo , Ke Yan , Tsung-Ying Ho , Jinzheng Cai , Adam P. Harrison , Xianghua Ye , Jing Xiao , Alan Yuille , Min Sun , Le Lu , Dakai Jin

Purpose: Identification of abdominal Lymph Nodes (LN) that are suspicious for metastasis in T2 Magnetic Resonance Imaging (MRI) scans is critical for staging of lymphoproliferative diseases. Prior work on LN detection has been limited to…

Image and Video Processing · Electrical Eng. & Systems 2022-04-05 Tejas Sudharshan Mathai , Sungwon Lee , Thomas C. Shen , Zhiyong Lu , Ronald M. Summers

Finding, identifying and segmenting suspicious cancer metastasized lymph nodes from 3D multi-modality imaging is a clinical task of paramount importance. In radiotherapy, they are referred to as Lymph Node Gross Tumor Volume (GTVLN).…

Image and Video Processing · Electrical Eng. & Systems 2020-08-28 Zhuotun Zhu , Dakai Jin , Ke Yan , Tsung-Ying Ho , Xianghua Ye , Dazhou Guo , Chun-Hung Chao , Jing Xiao , Alan Yuille , Le Lu

Purpose: Lymph nodes (LNs) in the chest have a tendency to enlarge due to various pathologies, such as lung cancer or pneumonia. Clinicians routinely measure nodal size to monitor disease progression, confirm metastatic cancer, and assess…

Image and Video Processing · Electrical Eng. & Systems 2024-01-15 Tejas Sudharshan Mathai , Bohan Liu , Ronald M. Summers

Metastasis on lymph nodes (LNs), the most common way of spread for primary tumor cells, is a sign of increased mortality. However, metastatic LNs are time-consuming and challenging to detect even for professional radiologists due to their…

Image and Video Processing · Electrical Eng. & Systems 2023-01-10 Chaoyi Wu , Feng Chang , Xiao Su , Zhihan Wu , Yanfeng Wang , Ling Zhu , Ya Zhang

We propose a fully-automated method for accurate and robust detection and segmentation of potentially cancerous lesions found in the liver and in lymph nodes. The process is performed in three steps, including organ detection, lesion…

Computer Vision and Pattern Recognition · Computer Science 2017-03-21 Assaf Hoogi , John W. Lambert , Yefeng Zheng , Dorin Comaniciu , Daniel L. Rubin

Lymph node (LN) assessment is an essential task in the routine radiology workflow, providing valuable insights for cancer staging, treatment planning and beyond. Identifying scatteredly-distributed and low-contrast LNs in 3D CT scans is…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Qinji Yu , Yirui Wang , Ke Yan , Dandan Zheng , Dashan Ai , Dazhou Guo , Zhanghexuan Ji , Yanzhou Su , Yun Bian , Na Shen , Xiaowei Ding , Le Lu , Xianghua Ye , Dakai Jin

Automatic lymph node segmentation is the cornerstone for advances in computer vision tasks for early detection and staging of cancer. Traditional segmentation methods are constrained by manual delineation and variability in operator…

Image and Video Processing · Electrical Eng. & Systems 2025-06-11 Jingguo Qu , Xinyang Han , Man-Lik Chui , Yao Pu , Simon Takadiyi Gunda , Ziman Chen , Jing Qin , Ann Dorothy King , Winnie Chiu-Wing Chu , Jing Cai , Michael Tin-Cheung Ying

Identification of lymph nodes (LN) in T2 Magnetic Resonance Imaging (MRI) is an important step performed by radiologists during the assessment of lymphoproliferative diseases. The size of the nodes play a crucial role in their staging, and…

Image and Video Processing · Electrical Eng. & Systems 2021-11-10 Tejas Sudharshan Mathai , Sungwon Lee , Daniel C. Elton , Thomas C. Shen , Yifan Peng , Zhiyong Lu , Ronald M. Summers

Objective: In clinical practice, small lung nodules can be easily overlooked by radiologists. The paper aims to provide an efficient and accurate detection system for small lung nodules while keeping good performance for large nodules.…

Image and Video Processing · Electrical Eng. & Systems 2021-06-09 Sunyi Zheng , Ludo J. Cornelissen , Xiaonan Cui , Xueping Jing , Raymond N. J. Veldhuis , Matthijs Oudkerk , Peter M. A. van Ooijen

Finding and identifying scatteredly-distributed, small, and critically important objects in 3D oncology images is very challenging. We focus on the detection and segmentation of oncology-significant (or suspicious cancer metastasized) lymph…

Computer Vision and Pattern Recognition · Computer Science 2020-05-29 Zhuotun Zhu , Ke Yan , Dakai Jin , Jinzheng Cai , Tsung-Ying Ho , Adam P Harrison , Dazhou Guo , Chun-Hung Chao , Xianghua Ye , Jing Xiao , Alan Yuille , Le Lu

Early detection of lung cancer is crucial for effective treatment and relies on accurate volumetric assessment of pulmonary nodules in CT scans. Traditional methods, such as consolidation-to-tumor ratio (CTR) and spherical approximation,…

Image and Video Processing · Electrical Eng. & Systems 2025-08-29 Yihan Zhou , Haocheng Huang , Yue Yu , Jianhui Shang

Quantification of lymphoid aggregates including tertiary lymphoid structures with germinal centers in histology images of cancer is a promising approach for developing prognostic and predictive tissue biomarkers. In this article, we provide…

Tissues and Organs · Quantitative Biology 2024-03-08 Karina Silina , Francesco Ciompi

Accurate assessment of Lung nodules is a time consuming and error prone ingredient of the radiologist interpretation work. Automating 3D volume detection and segmentation can improve workflow as well as patient care. Previous works have…

Image and Video Processing · Electrical Eng. & Systems 2019-07-29 Evi Kopelowitz , Guy Engelhard
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