Radiology, Nuclear Medicine & Medical Imaging

799.4K Papers

Follow See full results

Editorial Material Radiology, Nuclear Medicine & Medical Imaging

Understanding breast cancer as a global health concern

Louise Wilkinson, Toral Gathani

Summary: Breast cancer is the most commonly diagnosed cancer in the world, with a strong correlation to human development. Survival rates are lower in less developed regions, leading to global disparities. In order to address this urgent global health challenge, the World Health Organization has launched a new Global Breast Cancer Initiative, aiming to improve survival rates worldwide through health promotion, timely diagnosis, and comprehensive treatment and supportive care.

BRITISH JOURNAL OF RADIOLOGY (2022)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

First Clinical Photon-counting Detector CT System: Technical Evaluation

Kishore Rajendran, Martin Petersilka, Andre Henning, Elisabeth R. Shanblatt, Bernhard Schmidt, Thomas G. Flohr, Andrea Ferrero, Francis Baffour, Felix E. Diehn, Lifeng Yu, Prabhakar Rajiah, Joel G. Fletcher, Shuai Leng, Cynthia H. McCollough

Summary: This study assessed the technical performance of a clinical photon-counting detector (PCD) CT system, including noise, spatial resolution, and iodine CT number accuracy. The results showed that the PCD CT system has improved technical performance compared to current CT systems, with better temporal resolution and image quality in cardiac imaging.

RADIOLOGY (2022)

Add to Collection

Article Computer Science, Interdisciplinary Applications

Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis

Richard J. Chen, Ming Y. Lu, Jingwen Wang, Drew F. K. Williamson, Scott J. Rodig, Neal Lindeman, Faisal Mahmood

Summary: This study proposes an interpretable strategy for multimodal fusion of histology image and genomic features for survival outcome prediction. The results on glioma and clear cell renal cell carcinoma datasets demonstrate that this approach improves the prognostic determinations.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2022)

Add to Collection

Article Computer Science, Artificial Intelligence

FAT-Net: Feature adaptive transformers for automated skin lesion segmentation

Huisi Wu, Shihuai Chen, Guilian Chen, Wei Wang, Baiying Lei, Zhenkun Wen

Summary: The study introduces a novel skin lesion segmentation method named FAT-Net, which integrates transformer branch and feature adaptation module to capture long-range dependencies and enhance feature fusion. Experimental results demonstrate the superior accuracy and inference speed of FAT-Net on four public datasets compared to state-of-the-art methods.

MEDICAL IMAGE ANALYSIS (2022)

Add to Collection

Article Computer Science, Artificial Intelligence

Explainable artificial intelligence (XAI) in deep learning-based medical image analysis

Bas H. M. Van der Velden, Hugo J. Kuijf, Kenneth G. A. Gilhuijs, Max A. Viergever

Summary: This survey examines the applications of explainable artificial intelligence (XAI) in deep learning-based medical image analysis. It introduces a framework for classifying deep learning-based medical image analysis methods based on XAI criteria. The survey also categorizes and investigates XAI techniques in medical image analysis according to the framework and anatomical location. The paper concludes by discussing future opportunities for XAI in medical image analysis.

MEDICAL IMAGE ANALYSIS (2022)

Add to Collection

Article Engineering, Biomedical

Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation

Michael Yeung, Evis Sala, Carola-Bibiane Schoenlieb, Leonardo Rundo

Summary: Automatic segmentation methods using deep neural networks have advanced medical image analysis. However, class imbalance in medical datasets poses a challenge for model convergence. In this study, we propose the Unified Focal loss function to handle class imbalance and demonstrate its superior performance compared to other loss functions on various medical imaging datasets.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2022)

Add to Collection

Article Computer Science, Artificial Intelligence

Recent advances and clinical applications of deep learning in medical image analysis

Xuxin Chen, Ximin Wang, Ke Zhang, Kar-Ming Fung, Theresa C. Thai, Kathleen Moore, Robert S. Mannel, Hong Liu, Bin Zheng, Yuchen Qiu

Summary: This paper reviews the recent studies on applying deep learning methods in medical image analysis, emphasizing the latest progress and contributions of state-of-the-art unsupervised and semi-supervised deep learning in this field. It also discusses major technical challenges and suggests possible solutions for future research efforts.

MEDICAL IMAGE ANALYSIS (2022)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Feasibility, Biodistribution, and Preliminary Dosimetry in Peptide-Targeted Radionuclide Therapy of Diverse Adenocarcinomas Using 177Lu-FAP-2286: First-in-Humans Results

Richard P. Baum, Christiane Schuchardt, Aviral Singh, Maythinee Chantadisai, Franz C. Robiller, Jingjing Zhang, Dirk Mueller, Alexander Eismant, Frankis Almaguel, Dirk Zboralski, Frank Osterkamp, Aileen Hoehne, Ulrich Reineke, Christiane Smerling, Harshad R. Kulkarni

Summary: The study on Lu-177-FAP-2286 for peptide-targeted radionuclide therapy (PTRT) showed promising results in advanced adenocarcinoma patients, with a relatively good tolerability and acceptable side effects. Further prospective clinical studies are needed to confirm its efficacy.

JOURNAL OF NUCLEAR MEDICINE (2022)

Add to Collection

Editorial Material Radiology, Nuclear Medicine & Medical Imaging

ChatGPT and Other Large Language Models Are Double-edged Swords

Yiqiu Shen, Laura Heacock, Jonathan Elias, Keith D. Hentel, Beatriu Reig, George Shih, Linda Moy

RADIOLOGY (2023)

Add to Collection

Article Cardiac & Cardiovascular Systems

Effect of Evolocumab on Coronary Plaque Phenotype and Burden in Statin-Treated Patients Following Myocardial Infarction

Stephen J. Nicholls, Yu Kataoka, Steven E. Nissen, Francesco Prati, Stephan Windecker, Rishi Puri, Thomas Hucko, Daniel Aradi, Jean-Paul R. Herrman, Renicus S. Hermanides, Bei Wang, Huei Wang, Julie Butters, Giuseppe Di Giovanni, Stephen Jones, Gianluca Pompili, Peter J. Psaltis

Summary: The study on the use of evolocumab in combination with statins for patients with non-ST-segment elevation myocardial infarction showed that it can improve plaque composition in coronary arteries, with a stabilizing and regressive effect.

JACC-CARDIOVASCULAR IMAGING (2022)

Add to Collection

Article Neurosciences

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years

Sophia Frangou, Amirhossein Modabbernia, Steven C. R. Williams, Efstathios Papachristou, Gaelle E. Doucet, Ingrid Agartz, Moji Aghajani, Theophilus N. Akudjedu, Anton Albajes-Eizagirre, Dag Alnaes, Kathryn Alpert, Micael Andersson, Nancy C. Andreasen, Ole A. Andreassen, Philip Asherson, Tobias Banaschewski, Nuria Bargallo, Sarah Baumeister, Ramona Baur-Streubel, Alessandro Bertolino, Aurora Bonvino, Dorret Boomsma, Stefan Borgwardt, Josiane Bourque, Daniel Brandeis, Alan Breier, Henry Brodaty, Rachel M. Brouwer, Jan K. Buitelaar, Geraldo F. Busatto, Randy L. Buckner, Vincent Calhoun, Erick J. Canales-Rodriguez, Dara M. Cannon, Xavier Caseras, Francisco X. Castellanos, Simon Cervenka, Tiffany M. Chaim-Avancini, Christopher R. K. Ching, Victoria Chubar, Vincent P. Clark, Patricia Conrod, Annette Conzelmann, Benedicto Crespo-Facorro, Fabrice Crivello, Eveline A. Crone, Anders M. Dale, Christopher Davey, Eco J. C. de Geus, Lieuwe de Haan, Greig de Zubicaray, Anouk den Braber, Erin W. Dickie, Annabella Di Giorgio, Nhat Trung Doan, Erlend S. Dorum, Stefan Ehrlich, Susanne Erk, Thomas Espeseth, Helena Fatouros-Bergman, Simon E. Fisher, Jean-Paul Fouche, Barbara Franke, Thomas Frodl, Paola Fuentes-Claramonte, David C. Glahn, Ian H. Gotlib, Hans-Joergen Grabe, Oliver Grimm, Nynke A. Groenewold, Dominik Grotegerd, Oliver Gruber, Patricia Gruner, Rachel E. Gur, Ruben C. Gur, Ben J. Harrison, Catharine A. Hartman, Sean N. Hatton, Andreas Heinz, Dirk J. Heslenfeld, Derrek P. Hibar, Ian B. Hickie, Beng-Choon Ho, Pieter J. Hoekstra, Sarah Hohmann, Avram J. Holmes, Martine Hoogman, Norbert Hosten, Fleur M. Howells, Hilleke E. Hulshoff Pol, Chaim Huyser, Neda Jahanshad, Anthony James, Terry L. Jernigan, Jiyang Jiang, Erik G. Jonsson, John A. Joska, Rene Kahn, Andrew Kalnin, Ryota Kanai, Marieke Klein, Tatyana P. Klyushnik, Laura Koenders, Sanne Koops, Bernd Kraemer, Jonna Kuntsi, Jim Lagopoulos, Luisa Lazaro, Irina Lebedeva, Won Hee Lee, Klaus-Peter Lesch, Christine Lochner, Marise W. J. Machielsen, Sophie Maingault, Nicholas G. Martin, Ignacio Martinez-Zalacain, David Mataix-Cols, Bernard Mazoyer, Colm McDonald, Brenna C. McDonald, Andrew M. McIntosh, Katie L. McMahon, Genevieve McPhilemy, Jose M. Menchon, Sarah E. Medland, Andreas Meyer-Lindenberg, Jilly Naaijen, Pablo Najt, Tomohiro Nakao, Jan E. Nordvik, Lars Nyberg, Jaap Oosterlaan, Victor Ortiz-Garcia de la Foz, Yannis Paloyelis, Paul Pauli, Giulio Pergola, Edith Pomarol-Clotet, Maria J. Portella, Steven G. Potkin, Joaquim Radua, Andreas Reif, Daniel A. Rinker, Joshua L. Roffman, Pedro G. P. Rosa, Matthew D. Sacchet, Perminder S. Sachdev, Raymond Salvador, Pascual Sanchez-Juan, Salvador Sarro, Theodore D. Satterthwaite, Andrew J. Saykin, Mauricio H. Serpa, Lianne Schmaal, Knut Schnell, Gunter Schumann, Kang Sim, Jordan W. Smoller, Iris Sommer, Carles Soriano-Mas, Dan J. Stein, Lachlan T. Strike, Suzanne C. Swagerman, Christian K. Tamnes, Henk S. Temmingh, Sophia Thomopoulos, Alexander S. Tomyshev, Diana Tordesillas-Gutierrez, Julian N. Trollor, Jessica A. Turner, Anne Uhlmann, Odile A. van den Heuvel, Dennis van den Meer, Nic J. A. van der Wee, Neeltje E. M. van Haren, Dennis van't Ent, Theo G. M. van Erp, Ilya M. Veer, Dick J. Veltman, Aristotle Voineskos, Henry Voelzke, Henrik Walter, Esther Walton, Lei Wang, Yang Wang, Thomas H. Wassink, Bernd Weber, Wei Wen, John D. West, Lars T. Westlye, Heather Whalley, Lara M. Wierenga, Katharina Wittfeld, Daniel H. Wolf, Amanda Worker, Margaret J. Wright, Kun Yang, Yulyia Yoncheva, Marcus Zanetti, Georg C. Ziegler, Paul M. Thompson, Danai Dima

Summary: The study used data from the ENIGMA Consortium to explore the relationship between age and cortical thickness, finding that most regions peak in cortical thickness during childhood, with a negative association between age and cortical thickness where the slope is steeper before the age of 30 and more gradual afterwards.

HUMAN BRAIN MAPPING (2022)

Add to Collection

Editorial Material Radiology, Nuclear Medicine & Medical Imaging

ChatGPT and the Future of Medical Writing

Som Biswas

RADIOLOGY (2023)

Add to Collection

Article Acoustics

Quartz tuning forks resonance frequency matching for laser spectroscopy sensing

Yufei Ma, Yinqiu Hu, Shunda Qiao, Ziting Lang, Xiaonan Liu, Ying He, Vincenzo Spagnolo

Summary: This paper reports on the performance of quartz tuning fork (QTF) based laser spectroscopy sensing using multiple QTFs. Two resonance frequency matching methods are proposed to avoid degradation of sensor performance. Experimental results validate the effectiveness of the proposed methods.

PHOTOACOUSTICS (2022)

Add to Collection

Review Radiology, Nuclear Medicine & Medical Imaging

Transfer learning for medical image classification: a literature review

Hee E. Kim, Alejandro Cosa-Linan, Nandhini Santhanam, Mahboubeh Jannesari, Mate E. Maros, Thomas Ganslandt

Summary: Transfer learning with convolutional neural networks has made significant contributions to medical image analysis by leveraging prior knowledge from similar tasks to improve performance on new tasks. This review paper provides guidance on selecting models and transfer learning approaches for medical image classification. The majority of studies evaluated multiple models empirically, with deep models like Inception being the most commonly used. Deep models as feature extractors, such as ResNet or Inception, are recommended to save computational costs and time without compromising predictive power.

BMC MEDICAL IMAGING (2022)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Initial Clinical Experience with 90Y-FAPI-46 Radioligand Therapy for Advanced-Stage Solid Tumors: A Case Series of 9 Patients

Justin Ferdinandus, Pedro Fragoso Costa, Lukas Kessler, Manuel Weber, Nader Hirmas, Karina Kostbade, Sebastian Bauer, Martin Schuler, Marit Ahrens, Hans-Ulrich Schildhaus, Christoph Rischpler, Hong Grafe, Jens T. Siveke, Ken Herrmann, Wolfgang P. Fendler, Rainer Hamacher

Summary: This study investigates the feasibility and safety of Y-90-FAPI-46 radioligand therapy in patients with solid tumors. The results demonstrate good tolerability and a low rate of adverse events. Furthermore, the low radiation doses to at-risk organs suggest the possibility of repeat cycles of Y-90-FAPI-46.

JOURNAL OF NUCLEAR MEDICINE (2022)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Breast cancer screening in women with extremely dense breasts recommendations of the European Society of Breast Imaging (EUSOBI)

Ritse M. Mann, Alexandra Athanasiou, Pascal A. T. Baltzer, Julia Camps-Herrero, Paola Clauser, Eva M. Fallenberg, Gabor Forrai, Michael H. Fuchsjaeger, Thomas H. Helbich, Fleur Killburn-Toppin, Mihai Lesaru, Pietro Panizza, Federica Pediconi, Ruud M. Pijnappel, Katja Pinker, Francesco Sardanelli, Tamar Sella, Isabelle Thomassin-Naggara, Sophia Zackrisson, Fiona J. Gilbert, Christiane K. Kuhl

Summary: Breast density is an independent risk factor for breast cancer and reduces the effectiveness of mammography. Recent studies show that contrast-enhanced breast MRI can significantly reduce breast cancer mortality and is cost-effective for women with extremely dense breasts. Therefore, the European Society of Breast Imaging (EUSOBI) recommends informing women about their breast density and offering screening breast MRI every 2 to 4 years for women aged 50 to 70 with extremely dense breasts.

EUROPEAN RADIOLOGY (2022)

Add to Collection

Article Acoustics

Ultra-highly sensitive HCl-LITES sensor based on a low-frequency quartz tuning fork and a fiber-coupled multi-pass cell

Shunda Qiao, Angelo Sampaolo, Pietro Patimisco, Vincenzo Spagnolo, Yufei Ma

Summary: In this paper, an ultra-highly sensitive light-induced thermoelastic spectroscopy (LITES) based HCl sensor using a custom low-frequency QTF and a fiber-coupled MPC was demonstrated. The results showed that the low-frequency QTF provided improved signal enhancement compared to a standard QTF, and the fiber-coupled MPC enhanced system robustness. The sensor exhibited an excellent linear response to HCl gas concentration.

PHOTOACOUSTICS (2022)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Performance Characteristics of the Biograph Vision Quadra PET/CT System with a Long Axial Field of View Using the NEMA NU 2-2018 Standard

George A. Prenosil, Hasan Sari, Markus Furstner, Ali Afshar-Oromieh, Kuangyu Shi, Axel Rominger, Michael Hentschel

Summary: The performance of the Biograph Vision Quadra PET/CT system was evaluated in this study. The system showed improved sensitivity and count rates compared to the Biograph Vision 600 due to its larger field of view. The physical performance and image quality were assessed through various experiments and compared with existing PET scanners.

JOURNAL OF NUCLEAR MEDICINE (2022)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Accelerate gas diffusion-weighted MRI for lung morphometry with deep learning

Caohui Duan, He Deng, Sa Xiao, Junshuai Xie, Haidong Li, Xiuchao Zhao, Dongshan Han, Xianping Sun, Xin Lou, Chaohui Ye, Xin Zhou

Summary: The study accelerated multiple b-value gas DW-MRI using deep learning, achieving high-quality reconstructions with faster speed. The DC-RDN demonstrated effectiveness in maintaining accurate estimation of lung microstructural morphometry, showing great potential for studying lung diseases in the future.

EUROPEAN RADIOLOGY (2022)

Add to Collection

Article Cardiac & Cardiovascular Systems

Multi-modality imaging assessment of native valvular regurgitation: an EACVI and ESC council of valvular heart disease position paper

Patrizio Lancellotti, Philippe Pibarot, John Chambers, Giovanni La Canna, Mauro Pepi, Raluca Dulgheru, Mark Dweck, Victoria Delgado, Madalina Garbi, Mani A. Vannan, David Montaigne, Luigi Badano, Pal Maurovich-Horvat, Gianluca Pontone, Alec Vahanian, Erwan Donal, Bernard Cosyns

Summary: This article presents clinical guidance for the multi-modality imaging assessment of native valvular regurgitation, including quantification of regurgitation, assessment of valve anatomy and function, and evaluation of the consequences on cardiac chambers. Imaging results play a crucial role in the management of patients with valvular regurgitation.

EUROPEAN HEART JOURNAL-CARDIOVASCULAR IMAGING (2022)

Add to Collection

«
1
2
3
4
5
»

See full results

Related Categories

Anesthesiology (212.5K) Audiology & Speech-Language Pathology (1.7K) Clinical Neurology (1.3M) Critical Care Medicine (338.4K) Dentistry, Oral Surgery & Medicine (340.8K) Dermatology (413.6K) Emergency Medicine (142.9K) Endocrinology & Metabolism (751.7K) Gastroenterology & Hepatology (856.4K) Geriatrics & Gerontology (226.3K) Gerontology (158.2K) Health Care Sciences & Services (433.8K) Hematology (653.3K) Immunology (896.7K) Infectious Diseases (453.2K) Integrative & Complementary Medicine (99.8K) Medical Ethics (26.6K) Medical Informatics (100.5K) Medical Laboratory Technology (108K) Medicine, General & Internal (1.3M) Medicine, Legal (48.4K) Medicine, Research & Experimental (710K) Nursing (297.8K) Obstetrics & Gynecology (559.8K) Oncology (1.8M) Ophthalmology (452.2K) Orthopedics (359.5K) Otorhinolaryngology (166K) Pediatrics (655.3K) Peripheral Vascular Disease (595.7K) Pharmacology & Pharmacy (1.3M) Primary Health Care (59.2K) Psychiatry (755.1K) Rehabilitation (249.2K) Rheumatology (300.3K) Surgery (1.3M) Toxicology (333.1K) Transplantation (309.7K) Tropical Medicine (112.2K) Urology & Nephrology (567K) Veterinary Sciences (455.3K)

© Peeref 2019-2024. All rights reserved.