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Journal of Imaging Informatics in Medicine

Ausgabe 1/2023

Inhalt (31 Artikel)

Original Paper

Imaging Informatics Fellowship Curriculum: Building Consensus on the Most Critical Topics and the Future of the Informatics Fellowship

Roger Gerard, Valeria Makeeva, Brianna Vey, Tessa S. Cook, Paul Nagy, Ross W. Filice, Kenneth C. Wang, Patricia Balthazar, Peter Harri, Nabile M. Safdar

Original Paper

Artificial Intelligence-Powered Clinical Decision Support and Simulation Platform for Radiology Trainee Education

Chintan Shah, Karapet Davtyan, Ilya Nasrallah, R Nick Bryan, Suyash Mohan

Open Access Original Paper

Fidelity of 3D Printed Brains from MRI Scan in Children with Pathology (Prior Hypoxic Ischemic Injury)

Anith Chacko, Phassawan Rungsiprakarn, Ivan Erlic, Ngoc Jade Thai, Savvas Andronikou

Reducing Wait Times for Radiology Exams Around Holiday Periods: A Monte Carlo Simulation

Vivek A. Pisharody, Hooman Yarmohammadi, Etay Ziv, Vlasios S. Sotirchos, Erica Alexander, Constantino Sofocleous, Joseph P. Erinjeri

Original Paper

Artificial Humming Bird Optimization–Based Hybrid CNN-RNN for Accurate Exudate Classification from Fundus Images

Dhiravidachelvi E., Senthil Pandi S., Prabavathi R., Bala Subramanian C.

Original Paper

Recognition of Digital Dental X-ray Images Using a Convolutional Neural Network

Feng Liu, Lei Gao, Jun Wan, Zhi-Lei Lyu, Ying-Ying Huang, Chao Liu, Min Han

Original Paper

Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Technique

Seyed Ali Reza Moezzi, Abdolrahman Ghaedi, Mojdeh Rahmanian, Seyedeh Zahra Mousavi, Ashkan Sami

Original Paper

Event-Based Clinical Finding Extraction from Radiology Reports with Pre-trained Language Model

Wilson Lau, Kevin Lybarger, Martin L. Gunn, Meliha Yetisgen

Original Paper

Natural Language Processing Model for Identifying Critical Findings—A Multi-Institutional Study

Imon Banerjee, Melissa A. Davis, Brianna L. Vey, Sina Mazaheri, Fiza Khan, Vaz Zavaletta, Roger Gerard, Judy Wawira Gichoya, Bhavik Patel

Original Paper

Deep Learning for Detection of Intracranial Aneurysms from Computed Tomography Angiography Images

Xiujuan Liu, Jun Mao, Ning Sun, Xiangrong Yu, Lei Chai, Ye Tian, Jianming Wang, Jianchao Liang, Haiquan Tao, Lihua Yuan, Jiaming Lu, Yang Wang, Bing Zhang, Kaihua Wu, Yiding Wang, Mengjiao Chen, Zhishun Wang, Ligong Lu

Open Access

Intra-operator Repeatability of Manual Segmentations of the Hip Muscles on Clinical Magnetic Resonance Images

Giorgio Davico, Francesca Bottin, Alberto Di Martino, Vanita Castafaro, Fabio Baruffaldi, Cesare Faldini, Marco Viceconti

Original Paper

Toward Robust Partial-Image Based Template Matching Techniques for MRI-Guided Interventions

Eung-Joo Lee, Setareh Farzinfard, Pavel Yarmolenko, Kevin Cleary, Reza Monfaredi

COVID-19 Original Paper

Deep Learning–Based Time-to-Death Prediction Model for COVID-19 Patients Using Clinical Data and Chest Radiographs

Toshimasa Matsumoto, Shannon Leigh Walston, Michael Walston, Daijiro Kabata, Yukio Miki, Masatsugu Shiba, Daiju Ueda

An Explainable Convolutional Neural Network for the Early Diagnosis of Alzheimer’s Disease from 18F-FDG PET

Lisa Anita De Santi, Elena Pasini, Maria Filomena Santarelli, Dario Genovesi, Vincenzo Positano

Open Access Review

Deep Learning for Image Enhancement and Correction in Magnetic Resonance Imaging—State-of-the-Art and Challenges

Zhaolin Chen, Kamlesh Pawar, Mevan Ekanayake, Cameron Pain, Shenjun Zhong, Gary F. Egan

Open Access Original Paper

Accelerated Diffusion-Weighted MR Image Reconstruction Using Deep Neural Networks

Fariha Aamir, Ibtisam Aslam, Madiha Arshad, Hammad Omer

Original Paper

Improving the Automatic Classification of Brain MRI Acquisition Contrast with Machine Learning

Julia Cluceru, Janine M. Lupo, Yannet Interian, Riley Bove, Jason C. Crane

Original Paper

Automated Multimodal Machine Learning for Esophageal Variceal Bleeding Prediction Based on Endoscopy and Structured Data

Yu Wang, Yu Hong, Yue Wang, Xin Zhou, Xin Gao, Chenyan Yu, Jiaxi Lin, Lu Liu, Jingwen Gao, Minyue Yin, Guoting Xu, Xiaolin Liu, Jinzhou Zhu

Original Paper

U-Patch GAN: A Medical Image Fusion Method Based on GAN

Chao Fan, Hao Lin, Yingying Qiu

Original Paper

Definition of the Region of Interest for the Assessment of Alveolar Bone Repair Using Micro-computed Tomography

Juliana Simeão Borges, Vitor Cardoso Costa, Milena Suemi Irie, Gabriella Lopes de Rezende Barbosa, Rubens Spin-Neto, Priscilla Barbosa Ferreira Soares

The 2021 SIIM-FISABIO-RSNA Machine Learning COVID-19 Challenge: Annotation and Standard Exam Classification of COVID-19 Chest Radiographs

Paras Lakhani, J. Mongan, C. Singhal, Q. Zhou, K. P. Andriole, W. F. Auffermann, P. M. Prasanna, T. X. Pham, Michael Peterson, P. J. Bergquist, T. S. Cook, S. F. Ferraciolli, G. C. A. Corradi, MS Takahashi, C. S. Workman, M. Parekh, S. I. Kamel, J. Galant, A. Mas-Sanchez, E. C. Benítez, M. Sánchez-Valverde, L. Jaques, M. Panadero, M. Vidal, M. Culiañez-Casas, D. Angulo-Gonzalez, S. G. Langer, María de la Iglesia-Vayá, G. Shih

Non-Expert Markings of Active Chronic Graft-Versus-Host Disease Photographs: Optimal Metrics of Training Effects

Kelsey Parks, Xiaoqi Liu, Tahsin Reasat, Zain Khera, Laura X. Baker, Heidi Chen, Benoit M. Dawant, Inga Saknite, Eric R. Tkaczyk

Screening-Mammografie offenbart erhöhtes Herz-Kreislauf-Risiko

26.04.2024 Mammografie Nachrichten

Routinemäßige Mammografien helfen, Brustkrebs frühzeitig zu erkennen. Anhand der Röntgenuntersuchung lassen sich aber auch kardiovaskuläre Risikopatientinnen identifizieren. Als zuverlässiger Anhaltspunkt gilt die Verkalkung der Brustarterien.

S3-Leitlinie zu Pankreaskrebs aktualisiert

23.04.2024 Pankreaskarzinom Nachrichten

Die Empfehlungen zur Therapie des Pankreaskarzinoms wurden um zwei Off-Label-Anwendungen erweitert. Und auch im Bereich der Früherkennung gibt es Aktualisierungen.

Fünf Dinge, die im Kindernotfall besser zu unterlassen sind

18.04.2024 Pädiatrische Notfallmedizin Nachrichten

Im Choosing-Wisely-Programm, das für die deutsche Initiative „Klug entscheiden“ Pate gestanden hat, sind erstmals Empfehlungen zum Umgang mit Notfällen von Kindern erschienen. Fünf Dinge gilt es demnach zu vermeiden.

„Nur wer sich gut aufgehoben fühlt, kann auch für Patientensicherheit sorgen“

13.04.2024 Klinik aktuell Kongressbericht

Die Teilnehmer eines Forums beim DGIM-Kongress waren sich einig: Fehler in der Medizin sind häufig in ungeeigneten Prozessen und mangelnder Kommunikation begründet. Gespräche mit Patienten und im Team können helfen.

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