Reproducibility in machine learning for medical imaging
Reproducibility is a cornerstone of science, as the replication of findings is the process
through which they become knowledge. It is widely considered that many fields of science …
through which they become knowledge. It is widely considered that many fields of science …
Automatic motion artefact detection in brain T1-weighted magnetic resonance images from a clinical data warehouse using synthetic data
Containing the medical data of millions of patients, clinical data warehouses (CDWs)
represent a great opportunity to develop computational tools. Magnetic resonance images …
represent a great opportunity to develop computational tools. Magnetic resonance images …
Maximizing domain generalization in fetal brain tissue segmentation: the role of synthetic data generation, intensity clustering and real image fine-tuning
Fetal brain tissue segmentation in magnetic resonance imaging (MRI) is a crucial tool that
supports the understanding of neurodevelopment, yet it faces challenges due to the …
supports the understanding of neurodevelopment, yet it faces challenges due to the …
Recent advances in the open-source ClinicaDL software for reproducible neuroimaging with deep learning
R Hassanaly, C Brianceau, M Diaz… - Medical Imaging …, 2024 - spiedigitallibrary.org
In this paper, we present ClinicaDL, an open-source software platform that aims at
enhancing the reproducibility and rigor of research for deep learning in neuroimaging. We …
enhancing the reproducibility and rigor of research for deep learning in neuroimaging. We …
Methods of Increasing Training Data for a 3D Neural Network for Alzheimer's Disease Diagnosis
VO Yachnaya, MA Mikhalkova - 2024 Wave Electronics and its …, 2024 - ieeexplore.ieee.org
Alzheimer's disease (AD) is the most common cause of dementia among older adults. As it is
associated with brain cell death and mass losses, deep learning and computer vision are …
associated with brain cell death and mass losses, deep learning and computer vision are …
Leveraging noise and contrast simulation for the automatic quality control of routine clinical T1-weighted brain MRI
S Loizillon, S Mabille, S Bottani… - Medical Imaging …, 2024 - spiedigitallibrary.org
The recent advent of clinical data warehouses (CDWs) has facilitated the sharing of very
large volumes of medical data for research purposes. MRIs can be affected by various …
large volumes of medical data for research purposes. MRIs can be affected by various …
Methods and frameworks of annotation cost optimization for deep learning algorithms applied to medical imaging
C Ruppli - 2023 - theses.hal.science
In recent years, the amount of medical imaging data has kept on growing. In 1980, 30
minutes of acquisition were necessary to obtain 40 medical images. Today, 1000 images …
minutes of acquisition were necessary to obtain 40 medical images. Today, 1000 images …
Analysis of Principle and Applications of FFT in Medical Imaging Dataset
Y Du - Highlights in Science, Engineering and Technology, 2024 - drpress.org
The outbreak of novel infectious diseases usually resulted in the high number of death and
infectious. It is always in urge to develop a method that can detect and diagnose the disease …
infectious. It is always in urge to develop a method that can detect and diagnose the disease …