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Total 22265 results found since Jan 2013.
Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging
The collection and curation of large-scale medical datasets from multiple institutions is essential for training accurate deep learning models, but privacy concerns often hinder data sharing. Federated learning (FL) is a promising solution that enables privacy-preserving collaborative learning among different institutions, but it generally suffers from performance deterioration due to heterogeneous data distributions and a lack of quality labeled data. In this paper, we present a robust and label-efficient self-supervised FL framework for medical image analysis. Our method introduces a novel Transformer-based self-supervis...
Source: IEE Transactions on Medical Imaging - July 1, 2023 Category: Biomedical Engineering Source Type: research
Distributed deep learning networks among institutions for medical imaging
ConclusionsWe show that distributing deep learning models is an effective alternative to sharing patient data. This finding has implications for any collaborative deep learning study.
Source: Journal of the American Medical Informatics Association - March 29, 2018 Category: Information Technology Source Type: research
A Novel Algorithm for Hyperspectral Image Denoising in Medical Application
AbstractThe one of the preprocessing step for hyperspectral imagery is noise reduction. The images are received by the detector and this can be degraded by several factors like atmospherical things and device noises which emit temperature noise, processing noise and explosion noise. There are several strategies are developed already to cut back the signal to noise magnitude relation of the hyperspectral image. However, the stationary noise of the many denoising ways developed cannot be applied on to the gauge boson noise. Thus, the each gauge boson and thermal noise square measure gift within the captured hyperspectral ima...
Source: Journal of Medical Systems - July 22, 2019 Category: Information Technology Source Type: research
Anti-Interference From Noisy Labels: Mean-Teacher-Assisted Confident Learning for Medical Image Segmentation
Manually segmenting medical images is expertise-demanding, time-consuming and laborious. Acquiring massive high-quality labeled data from experts is often infeasible. Unfortunately, without sufficient high-quality pixel-level labels, the usual data-driven learning-based segmentation methods often struggle with deficient training. As a result, we are often forced to collect additional labeled data from multiple sources with varying label qualities. However, directly introducing additional data with low-quality noisy labels may mislead the network training and undesirably offset the efficacy provided by those high-quality la...
Source: IEE Transactions on Medical Imaging - October 28, 2022 Category: Biomedical Engineering Source Type: research
DLTTA: Dynamic Learning Rate for Test-Time Adaptation on Cross-Domain Medical Images
Test-time adaptation (TTA) has increasingly been an important topic to efficiently tackle the cross-domain distribution shift at test time for medical images from different institutions. Previous TTA methods have a common limitation of using a fixed learning rate for all the test samples. Such a practice would be sub-optimal for TTA, because test data may arrive sequentially therefore the scale of distribution shift would change frequently. To address this problem, we propose a novel dynamic learning rate adjustment method for test-time adaptation, called DLTTA, which dynamically modulates the amount of weights update for ...
Source: IEE Transactions on Medical Imaging - December 1, 2022 Category: Biomedical Engineering Source Type: research
Smartphone-based fundus imaging: applications and adapters
CONCLUSION: SBFI is a versatile, mobile, low-cost alternative to conventional equipment for color fundus photography. In addition, it facilitates the delegation of ophthalmological examinations to assistance personnel in telemedical settings, could simplify retinal documentation, improve teaching, and improve ophthalmological care, particularly in countries with low and middle incomes.PMID:34913992 | DOI:10.1007/s00347-021-01536-9
Source: Der Ophthalmologe - December 16, 2021 Category: Opthalmology Authors: Linus G Jansen Thomas Schultz Frank G Holz Robert P Finger Maximilian W M Wintergerst Source Type: research
Local food policies can help promote local foods and improve health: a case study from the Federated States of Micronesia
Hawaii Med J. 2011 Nov;70(11 Suppl 2):31-4.ABSTRACTThe Federated States of Micronesia (FSM) and other countries throughout the Pacific are facing an epidemic of non-communicable disease health problems. These are directly related to the increased consumption of unhealthy imported processed foods, the neglect of traditional food systems, and lifestyle changes, including decreased physical activity. The FSM faces the double burden of malnutrition with both non-communicable diseases and micronutrient deficiencies, including vitamin A deficiency and anemia. To help increase the use of traditional island foods and improve healt...
Source: Hawaii Medical Journal - January 12, 2012 Category: General Medicine Authors: Lois Englberger Adelino Lorens Moses Pretrick Mona J Tara Emihner Johnson Source Type: research
