Article
Ecology
Sara Arganda, Ignacio Arganda-Carreras, Darcy G. Gordon, Andrew P. Hoadley, Alfonso Perez-Escudero, Martin Giurfa, James F. A. Traniello
Summary: This article introduces three strategies for constructing statistical brain atlases using ants as a model taxon, and compares the accuracy of automatic and manual methods through volume similarity evaluation against human expert annotators, finding that they are equivalent.
FRONTIERS IN ECOLOGY AND EVOLUTION
(2022)
Review
Neurosciences
Alfredo Conti, Nicola Maria Gambadauro, Paolo Mantovani, Canio Pietro Picciano, Vittoria Rosetti, Marcello Magnani, Sebastiano Lucerna, Constantin Tuleasca, Pietro Cortelli, Giulia Giannini
Summary: Modern brain atlases derived from neuroimaging and functional information are crucial for accurate neurosurgical procedures. They help avoid targeting errors caused by imaging artifacts or insufficient anatomical details.
Article
Education & Educational Research
Kiran Kasper Rajan, Anand S. Pandit
Summary: This study compared the effectiveness of using an eModule and a Wikipedia-like webpage for medical education. The results showed that students found the eModule more engaging, useful, and enjoyable, with interactivity and clinical cases being the main contributing factors. However, there was no significant difference in learning efficacy between the eModule and Wikipedia groups.
BMC MEDICAL EDUCATION
(2022)
Article
History & Philosophy Of Science
Boleslav Lichterman, Douglas J. Lanska
Summary: Russian surgeon Nikolay Ivanovich Pirogov introduced applied topographical anatomy to Russia and published the monumental Ice Anatomy atlas in the 1850s. By freezing cadavers and cutting them into thin plates for detailed anatomical illustrations, Pirogov revolutionized anatomical studies with high-quality lithographs resembling modern medical imaging.
JOURNAL OF THE HISTORY OF THE NEUROSCIENCES
(2022)
Article
Neurosciences
Joel D. Hahn, Larry W. Swanson, Ian Bowman, Nicholas N. Foster, Brian Zingg, Michael S. Bienkowski, Houri Hintiryan, Hong-Wei Dong
Summary: This study presents flatmaps of the mouse, rat, and human brain, with enhanced representations of the nervous system components and different stages of rat brain development. These flatmaps serve as a neuroscience toolbox for researchers, facilitating comparative analysis of brain data.
JOURNAL OF COMPARATIVE NEUROLOGY
(2021)
Article
Environmental Sciences
William Yamada, Wei Zhao, Matthew Digman
Summary: An automatic method using monovision un-crewed aerial vehicle imagery was developed to obtain geographic coordinates of bales, with YOLOv3 algorithm identified as the best option in terms of accuracy and speed. Lowering image quality resulted in decreased performance.
Article
Computer Science, Interdisciplinary Applications
Akbar Bahari, Xue Zhang, Yuliya Ardasheva
Summary: Drawing on the nonlinearity and dynamicity of L2 motivation and individual differences, the study introduced and examined the CAIRM model, incorporating CALL tools to assist reading comprehension in blended and distance learning contexts. Results showed that combining bottom-up and top-down processing strategies was the most effective level of CAIRM implementation.
COMPUTERS & EDUCATION
(2021)
Article
Education, Scientific Disciplines
Ellen M. Robertson, Sara M. Allison, Caroline M. Mueller, Andrew C. Ferriby, Alex R. Roth, Ranjan Batra
Summary: The study aimed to determine the most effective method of brain removal based on time, difficulty, and preservation of key brain structures for educational purposes. The results showed little difference between different approaches for both calvaria removal and spinal cord transection. A circumferential cut was the most time-effective method for calvaria removal, while a posterior cut between C1 and C2 was the most time-effective and least difficult method for brainstem release.
ANATOMICAL SCIENCES EDUCATION
(2023)
Article
Surgery
R. B. den Boer, T. J. M. Jaspers, C. de Jongh, J. P. W. Pluim, F. van der Sommen, T. Boers, R. van Hillegersberg, M. A. J. M. Van Eijnatten, J. P. Ruurda
Summary: This study developed a deep learning algorithm to recognize anatomical structures in video frames from robot-assisted minimally invasive esophagectomy (RAMIE) procedures. It shows potential for clinical application and further prospective clinical studies are needed to assess its effectiveness.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2023)
Article
Geriatrics & Gerontology
Marcela Martins Chiudo, Patricia Bet, Giovana Fondato Costa, Maria Do Socorro Morais Pereira Simo, Moacir Antonelli Ponti, Victor Zuniga Dourado, Paula Costa Castro
Summary: This study aims to investigate the characteristics of human movement and its relationship with health conditions for different age groups. The results demonstrate that age, sex, demographic factors, anthropometric factors, and cardiovascular risk factors can affect human movement.
EXPERIMENTAL GERONTOLOGY
(2022)
Editorial Material
Education, Scientific Disciplines
Thomas H. Champney
Summary: With the development of CT, the orientation of neuroanatomy has changed, and the importance of the clinical view in medical education has been increasingly recognized.
ANATOMICAL SCIENCES EDUCATION
(2023)
Article
Engineering, Biomedical
Zhimin Shao, Weibei Dou, Di Ma, Xiaoxue Zhai, Quan Xu, Yu Pan
Summary: This study proposes a new method to more accurately estimate the influence of neuro-intervention on brain damage. By modeling left and right hemiplegia separately, the method shows a 5-15% improvement in accuracy compared to traditional methods, and reveals the common and unique recovery mechanisms after left and right strokes, assisting clinicians in formulating rehabilitation plans.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Article
Clinical Neurology
Muhammet Enes Gurses, Sahin Hanalioglu, Giancarlo Mignucci-Jimenez, Elif Gokalp, Nicolas I. Gonzalez-Romo, Abuzer Gungor, Aaron A. Cohen-Gadol, Ugur Ture, Michael T. Lawton, Mark C. Preul
Summary: Researchers utilized 360-degree photogrammetry to create high-resolution 3D models of intra-cerebral tissues and simulated them using augmented reality and virtual reality technologies. These models can be rotated, viewed from all angles, and examined at various magnifications on any surface. This study is important for neurosurgeons and students to better understand the 3D relationship of deep and superficial brain anatomy.
OPERATIVE NEUROSURGERY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Daniel Graefe, Stefan-Horia Simion, Maciej Rosolowski, Andreas Merkenschlager, Jens Frahm, Dirk Voit, Franz Wolfgang Hirsch
Summary: This study aimed to assess the deposition of gadobutrol in children and found evidence of its deposition in the globus pallidus and putamen.
EUROPEAN RADIOLOGY
(2023)
Article
Education, Scientific Disciplines
James D. Pickering, Antoniou Panagiotis, Georgios Ntakakis, Alkinoos Athanassiou, Emmanouil Babatsikos, Panagiotis D. Bamidis
Summary: The study examines the impact of a mixed reality application on neuroanatomy teaching, finding similar patterns of learner gain between groups but significantly higher performance on multiple-choice questionnaires in the screencast group. Despite limitations, the research provides important data supporting evidence-informed decisions for educators considering the inclusion of such resources in their curricula.
ANATOMICAL SCIENCES EDUCATION
(2022)
Article
Clinical Neurology
Stavros Tsagkaris, Eric K. C. Yau, Verity McClelland, Apostolos Papandreou, Ata Siddiqui, Daniel E. Lumsden, Margaret Kaminska, Eric Guedj, Alexander Hammers, Jean-Pierre Lin
Summary: Tsagkaris et al. found that patients with paediatric dystonia have different patterns of brain glucose metabolism observed through FDG-PET scans. These patterns can be linked to specific clinical signs and may serve as useful biomarkers for differential diagnosis and personalized management. The study sheds light on the pathophysiology of dystonia and supports the network theory for its development.
Letter
Clinical Neurology
Siti N. Yaakub, Tristan A. White, Eric Kerfoot, Lennart Verhagen, Alexander Hammers, Elsa F. Fouragnan
Article
Engineering, Electrical & Electronic
Kerstin Hammernik, Thomas Kustner, Burhaneddin Yaman, Zhengnan Huang, Daniel Rueckert, Florian Knoll, Mehmet Akcakaya
Summary: Physics-driven deep learning methods have revolutionized computational MRI reconstruction by improving the performance of reconstruction. This article provides an overview of recent developments in incorporating physics information into learning-based MRI reconstruction. It discusses both linear and non-linear forward models for computational MRI, classical approaches for solving these inverse problems, as well as physics-driven deep learning approaches such as physics-driven loss functions, plug-and-play methods, generative models, and unrolled networks. Challenges specific to MRI with linear and non-linear forward models are highlighted, and common issues and open challenges are also discussed.
IEEE SIGNAL PROCESSING MAGAZINE
(2023)
Article
Computer Science, Interdisciplinary Applications
Qiang Ma, Liu Li, Emma C. Robinson, Bernhard Kainz, Daniel Rueckert, Amir Alansary
Summary: CortexODE is a deep learning framework that uses neural ordinary differential equations (ODEs) to reconstruct cortical surfaces. By modeling the trajectories of points on the surface as ODEs and parameterizing the derivatives with a learnable deformation network, CortexODE is able to prevent self-intersections. Integrated with an automatic learning-based pipeline, CortexODE can efficiently reconstruct cortical surfaces in less than 5 seconds.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2023)
Article
Neurosciences
David Steinbart, Siti N. Yaakub, Mirja Steinbrenner, Lynn S. Guldin, Martin Holtkamp, Simon S. Keller, Bernd Weber, Theodor Rueber, Rolf Heckemann, Maria Ilyas-Feldmann, Alexander Hammers
Summary: This study proposes a manual segmentation protocol and an automatic segmentation method to investigate the relationship between the piriform cortex and memory as well as epilepsy. The results show differences in the volumes of the piriform cortex in healthy individuals, temporal lobe epilepsy patients, and Alzheimer's disease patients, providing a new biomarker for early diagnosis.
HUMAN BRAIN MAPPING
(2023)
Article
Computer Science, Interdisciplinary Applications
Cheng Ouyang, Chen Chen, Surui Li, Zeju Li, Chen Qin, Wenjia Bai, Daniel Rueckert
Summary: In this work, the authors investigate the problem of training a deep network that is robust to unseen domains using only data from one source domain. They propose a causality-inspired data augmentation approach to expose the model to synthesized domain-shifted training examples. The approach is validated on three cross-domain segmentation scenarios and shows consistent performance improvements compared to competitive methods.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2023)
Article
Computer Science, Artificial Intelligence
Tamara T. Mueller, Johannes C. Paetzold, Chinmay Prabhakar, Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis
Summary: Graph Neural Networks (GNNs) have become the state-of-the-art for many machine learning applications, but differentially private training of GNNs has remained under-explored. In this work, we propose a framework for differentially private graph-level classification using DP-SGD, which is applicable to multi-graph datasets.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Robert Wright, Alberto Gomez, Veronika A. Zimmer, Nicolas Toussaint, Bishesh Khanal, Jacqueline Matthew, Emily Skelton, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel
Summary: This paper introduces a novel method to fuse partially imaged fetal head anatomy from multiple views into a single coherent 3D volume. The method aligns and fuses ultrasound images to improve image detail and minimize artifacts, achieving state-of-the-art performance in terms of image quality and robustness.
MEDICAL IMAGE ANALYSIS
(2023)
Article
Psychiatry
Hai Le, Konstantina Dimitrakopoulou, Hamel Patel, Charles Curtis, Lucilio Cordero-Grande, A. David Edwards, Joseph Hajnal, Jacques-Donald Tournier, Maria Deprez, Harriet Cullen
Summary: Increasing evidence suggests that deviations from normal early development may contribute to the onset of schizophrenia in adolescence and young adulthood. This study examined brain imaging changes associated with schizophrenia variants in newborns. The results revealed negative associations between schizophrenia genetic risk scores and brain volumes in several regions, indicating possible involvement of schizophrenia risk genes in early brain growth.
TRANSLATIONAL PSYCHIATRY
(2023)
Article
Infectious Diseases
Michela Antonelli, Rose S. Penfold, Liane Dos Santos Canas, Carole Sudre, Khaled Rjoob, Ben Murray, Erika Molteni, Eric Kerfoot, Nathan Cheetham, Juan Capdevila Pujol, Lorenzo Polidori, Anna May, Jonathan Wolf, Marc Modat, Tim Spector, Alexander Hammers, Sebastien Ourselin, Claire Steves
Summary: This study describes the characteristics of SARS-CoV-2 illness following a third vaccination and assesses the risk of progression to symptomatic disease in SARS-CoV-2 infected individuals with time since vaccination. The results suggest that a third dose of monovalent vaccine may reduce symptoms, severity, and duration of SARS-CoV-2 infection following vaccination.
JOURNAL OF INFECTION
(2023)
Article
Cardiac & Cardiovascular Systems
Daniel Cromb, Alexandra F. Bonthrone, Alessandra Maggioni, Paul Cawley, Ralica Dimitrova, Christopher J. Kelly, Lucilio Cordero-Grande, Olivia Carney, Alexia Egloff, Emer Hughes, Joseph V. Hajnal, John Simpson, Kuberan Pushparajah, Mary A. Rutherford, A. David Edwards, Jonathan O'Muircheartaigh, Serena J. Counsell
Summary: Infants with congenital heart disease (CHD) are at risk of impaired brain growth, especially in the immediate postoperative period. The duration of postoperative intensive care stay is associated with the degree of impaired brain growth. Clinical risk factors, such as higher preoperative creatinine levels and longer cardiopulmonary bypass duration, are also associated with impaired brain growth.
JOURNAL OF THE AMERICAN HEART ASSOCIATION
(2023)
Review
Chemistry, Medicinal
Suresh Victor, Ben Forbes, Anne Greenough, A. David Edwards
Summary: Pioglitazone, an agonist of PPAR gamma, may have the potential to reduce the incidence of bronchopulmonary dysplasia and improve neurodevelopment in extreme preterm babies. However, there is currently no formulation of pioglitazone suitable for administration to preterm babies, and further development is needed before clinical trials can be conducted.
Article
Radiology, Nuclear Medicine & Medical Imaging
Guillaume Corda-D'Incan, Julia A. Schnabel, Alexander Hammers, Andrew J. Reader
Summary: We propose a new approach for deep learned joint PET-MR image reconstruction using a joint regularizer, which shows better performance compared to conventional synergistic methods and independent deep learned reconstruction methods. The investigation of loss function selection and the exploration of the impact of joint reconstruction on MR reconstruction are also conducted.
IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES
(2023)
Article
Computer Science, Interdisciplinary Applications
Adam Marcus, Paul Bentley, Daniel Rueckert
Summary: The proposed study introduces a novel end-to-end multi-task transformer-based model for concurrent segmentation and age estimation of cerebral ischemic lesions. The method captures long-range dependencies using gated positional self-attention and CT-specific data augmentation, and can be effectively trained with low-data regimes in medical imaging. Experimental results demonstrate promising performance in lesion age classification, outperforming existing task-specific algorithms.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2023)
Article
Computer Science, Artificial Intelligence
Jiazhen Pan, Manal Hamdi, Wenqi Huang, Kerstin Hammernik, Thomas Kuestner, Daniel Rueckert
Summary: This article introduces a learning-based and unrolled MCMR framework that can achieve accurate and rapid CMR reconstruction, delivering artifacts-free motion estimation and high-quality reconstruction even at imaging acceleration rates up to 20x.
MEDICAL IMAGE ANALYSIS
(2024)
