Article
Oncology
Petra K. de Koekkoek-Doll, Sander Roberti, Laura Smit, Wouter V. Vogel, Regina Beets-Tan, Michiel W. van den Brekel, Jonas Castelijns
Summary: Nodal staging in head and neck squamous cell carcinoma (HNSCC) is crucial for treatment and prognosis. Imaging tools such as FDG-PET, DW-MRI, and ultrasound-guided fine needle aspiration are commonly used. DW-MRI can aid in detecting small lymph node metastases, and there is potential for using ADC values to distinguish between cytologically reactive and malignant nodes.
Article
Medicine, General & Internal
Junko Inoue Inukai, Munenobu Nogami, Miho Tachibana, Feibi Zeng, Tatsuya Nishitani, Kazuhiro Kubo, Takamichi Murakami
Summary: This study evaluated the diagnostic value of a rapid whole-body FDG PET/MRI approach, combining BPL PET with an optimised beta value and abb-MRI. The study compared its diagnostic performance with standard PET/MRI that uses OSEM PET and std-MRI. Clinical evaluations and assessments were conducted in patients, and the results showed that the combined BPL/abb-MRI approach achieved rapid whole-body PET/MRI in <= 1.5 min per bed position while maintaining comparable diagnostic performance to standard PET/MRI.
Article
Multidisciplinary Sciences
Hongkai Wang, Yang Tian, Yang Liu, Zhaofeng Chen, Haoyu Zhai, Mingrui Zhuang, Nan Zhang, Yuanfang Jiang, Ya Gao, Hongbo Feng, Yanjun Zhang
Summary: The study enriched the family of publicly available brain PET templates by developing Chinese-specific template images based on [F-18]-FDG PET images of normal participants. The templates were validated through SPM analysis of Alzheimer's and Parkinson's patient images, accurately depicting disease-related brain regions with abnormal [F-18]-FDG uptake. The SPM analysis programmes developed also facilitated easy use of the templates, proving their effectiveness in brain function impairment analysis.
Article
Computer Science, Artificial Intelligence
Wei Shao, Linda Banh, Christian A. Kunder, Richard E. Fan, Simon J. C. Soerensen, Jeffrey B. Wang, Nikola C. Teslovich, Nikhil Madhuripan, Anugayathri Jawahar, Pejman Ghanouni, James D. Brooks, Geoffrey A. Sonn, Mirabela Rusu
Summary: Magnetic resonance imaging (MRI) is crucial in the diagnosis and treatment of prostate cancer, but suffers from high inter-observer variability. A deep learning-based pipeline, ProsRegNet, accelerates and simplifies MRI-histopathology image registration, providing accurate cancer labels mapping onto MRI.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Paolo Zanotti-Fregonara, Tatsuya Ishiguro, Kosuke Yoshihara, Shiro Ishii, Takayuki Enomoto
Summary: This study investigates the fetal absorbed dose from 18F-FDG administration in pregnant women using PET/MRI imaging. The results confirm that the fetal dose is very low, suggesting that clinically appropriate 18F-FDG scans should not be withheld due to pregnancy.
JOURNAL OF NUCLEAR MEDICINE
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yoshiharu Ohno, Takeshi Yoshikawa, Daisuke Takenaka, Hisanobu Koyama, Kota Aoyagi, Masao Yui, Yuka Oshima, Nayu Hamabuchi, Yumi Tanaka, Chika Shigemura, Seiichiro Oota, Masahiko Nomura, Kazuhiro Murayama, Yoshitaka Inui, Kaoru Kikukawa, Hiroshi Toyama
Summary: Whole-body MRI and FDG PET/MRI outperformed conventional staging tests and FOG PET/CT for staging of SCLC.
AMERICAN JOURNAL OF ROENTGENOLOGY
(2022)
Article
Oncology
Fei Wang, Rui Guo, Yan Zhang, Boqi Yu, Xiangxi Meng, Hanjing Kong, Yang Yang, Zhi Yang, Nan Li
Summary: This study investigated the value of F-18-FDG PET/MRI in the preoperative assessment of ESCC and compared it with other imaging methods. The results showed that F-18-FDG PET/MRI had higher accuracy and area under the curve in diagnosing primary tumors and regional lymph node metastases. Therefore, F-18-FDG PET/MRI may be a potential supplement or alternative imaging method for preoperative staging of ESCC.
FRONTIERS IN ONCOLOGY
(2022)
Article
Environmental Sciences
Lina Yi, Jing M. Chen, Guifeng Zhang, Xiao Xu, Xing Ming, Wenji Guo
Summary: This paper presents a systematic methodology for mosaicking hyperspectral images captured by UAV-based push-broom hyperspectral imagers, showcasing the importance of selecting appropriate registration and fusion methods based on different environmental areas for optimal results.
Article
Biology
Menglin Wu, Xuchen He, Fan Li, Jie Zhu, Shanshan Wang, Pablo D. Burstein
Summary: This study proposes a weakly-supervised deep learning volumetric registration approach that combines segmentations and signed distance maps (SDMs) as a mixed loss function. The method is robust to outliers and encourages optimal global alignment. Experimental results on a public prostate MRI-TRUS biopsy dataset demonstrate that the proposed method outperforms other weakly-supervised registration approaches.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Editorial Material
Radiology, Nuclear Medicine & Medical Imaging
Guohua Shen, Rang Wang, Lili Pan, Anren Kuang
Summary: Glomus tumors are vascular neoplasms arising from glomus bodies, typically found in tissues concentrated with these bodies. We reported the MRI and FDG PET/CT findings of a glomus tumor presenting as an axillary mass in a 25-year-old woman.
CLINICAL NUCLEAR MEDICINE
(2021)
Editorial Material
Radiology, Nuclear Medicine & Medical Imaging
Shiho Yokoo, Feibi Zeng, Munenobu Nogami, Yoshiko R. Ueno, Takamichi Murakami
Summary: A 52-year-old woman suspected of uterine sarcoma underwent F-18-FDG PET/MRI, which revealed a myometrial mass and an endometrial lesion, suggesting dual primary neoplasms. Based on the PET/MRI findings, the intraoperative procedure was modified to determine the necessity of pelvic lymphadenectomy. PET/MRI was more useful than PET/CT in diagnosing and differentiating between the two malignant neoplasms in the uterus, due to the high contrast resolution and precise fusion of MRI.
CLINICAL NUCLEAR MEDICINE
(2022)
Article
Computer Science, Artificial Intelligence
Han Xu, Jiteng Yuan, Jiayi Ma
Summary: This study proposes a novel method called MURF that mutually reinforces image registration and fusion. MURF consists of three modules, which progressively correct global and local offsets during the coarse-to-fine registration process and incorporate texture enhancement into image fusion. Extensive experiments validate the superiority and universality of MURF on different types of multi-modal data.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Thomas Hofer, Juergen Kronbichler, Helmut Huber, Benedikt Hergan, Bernhard Kaiser, Andreas Shamiyeh, Franz Fellner, Michael Gabriel
Summary: The study evaluated the diagnostic performance of F-18-choline PET and MRI in patients with primary hyperparathyroidism, with additional analysis of software-based PET/MRI scan fusion. F-18-choline PET/CT showed superior performance in localization diagnostics compared to MRI, with image fusion of both modalities providing more precise anatomical assignment.
CLINICAL NUCLEAR MEDICINE
(2021)
Editorial Material
Radiology, Nuclear Medicine & Medical Imaging
Sophia Huntley Antippa, Leanne Du, Nathan Price, Charlie Chia-Tsong Hsu
Summary: Recognition of the imaging pattern of hyoid ORN is crucial for avoiding misdiagnosis and enabling prompt treatment. Hyoid ORN is a rare complication following radiation treatment for head and neck malignancy, with limited cases described in the literature.
CLINICAL NUCLEAR MEDICINE
(2021)
Review
Oncology
Zhi Miao, Xiaomeng Zhao, Xuanwen Li
Summary: The purpose of this meta-analysis and systematic review was to compare the diagnostic performance of [18F]FDG PET/CT and [18F]FDG PET/MRI in colorectal liver metastasis. A total of 21 studies comprising 1036 patients were included. The results showed that [18F]FDG PET/CT and [18F]FDG PET/MRI have similar performance in detecting colorectal liver metastasis. However, larger prospective studies are needed due to limitations in the included studies.
FRONTIERS IN ONCOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Felix Lugauer, Dominik Nickel, Jens Wetzl, Berthold Kiefer, Joachim Hornegger, Andreas Maier
MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE
(2017)
Article
Engineering, Biomedical
Jessica Magaraggia, Wei Wei, Markus Weiten, Gerhard Kleinszig, Sven Vetter, Jochen Franke, Adrian John, Adrian Egli, Karl Barth, Elli Angelopoulou, Joachim Hornegger
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
(2017)
Article
Computer Science, Interdisciplinary Applications
Jian Wang, Roman Schaffert, Anja Borsdorf, Benno Heigl, Xiaolin Huang, Joachim Hornegger, Andreas Maier
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2017)
Article
Computer Science, Artificial Intelligence
Florin-Cristian Ghesu, Bogdan Georgescu, Yefeng Zheng, Sasa Grbic, Andreas Maier, Joachim Hornegger, Dorin Comaniciu
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2019)
Article
Radiology, Nuclear Medicine & Medical Imaging
Jens Wetzl, Michaela Schmidt, Francois Pontana, Benjamin Longere, Felix Lugauer, Andreas Maier, Joachim Hornegger, Christoph Forman
MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE
(2018)
Article
Computer Science, Interdisciplinary Applications
Peter Fischer, Anthony Faranesh, Thomas Pohl, Andreas Maier, Toby Rogers, Kanishka Ratnayaka, Robert Lederman, Joachim Hornegger
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2018)
Article
Radiology, Nuclear Medicine & Medical Imaging
Felix Lugauer, Jens Wetzl, Christoph Forman, Manuel Schneider, Berthold Kiefer, Joachim Hornegger, Dominik Nickel, Andreas Maier
MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE
(2018)
Article
Computer Science, Artificial Intelligence
Florin C. Ghesu, Bogdan Georgescu, Sasa Grbic, Andreas Maier, Joachim Hornegger, Dorin Comaniciu
MEDICAL IMAGE ANALYSIS
(2018)
Article
Computer Science, Artificial Intelligence
Franziska Schirrmacher, Thomas Koehler, Juergen Endres, Tobias Lindenberger, Lennart Husvogt, James G. Fujimoto, Joachim Hornegger, Arnd Doerfler, Philip Hoelter, Andreas K. Maier
MEDICAL IMAGE ANALYSIS
(2018)
Article
Computer Science, Artificial Intelligence
Xiaolin Huang, Johan A. K. Suykens, Shuning Wang, Joachim Hornegger, Andreas Maier
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2018)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yanye Lu, Markus Kowarschik, Xiaolin Huang, Yan Xia, Jang-Hwan Choi, Shuqing Chen, Shiyang Hu, Qiushi Ren, Rebecca Fahrig, Joachim Hornegger, Andreas Maier
Article
Radiology, Nuclear Medicine & Medical Imaging
Yanye Lu, Markus Kowarschik, Xiaolin Huang, Shuqing Chen, Qiushi Ren, Rebecca Fahrig, Joachim Hornegger, Andreas Maier
IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES
(2018)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yixing Huang, Xiaolin Huang, Oliver Taubmann, Yan Xia, Viktor Haase, Joachim Hornegger, Guenter Lauritsch, Andreas Maier
BIOMEDICAL PHYSICS & ENGINEERING EXPRESS
(2017)
Article
Engineering, Biomedical
M. Berger, Y. Xia, W. Aichinger, K. Mentl, M. Unberath, A. Aichert, C. Riess, J. Hornegger, R. Fahrig, A. Maier
PHYSICS IN MEDICINE AND BIOLOGY
(2017)
Article
Mathematics, Applied
Xiaolin Huang, Andreas Maier, Joachim Hornegger, Johan A. K. Suykens
APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS
(2017)