Current neuroimaging studies frequently use complex machine learning models to classify human fMRI data, distinguishing healthy and disordered brains, often to validate new methods or enhance prediction accuracy. Yet, where prediction accuracy is a c...
This article discusses the role of deep learning (DL) in cancer imaging, focusing on its applications for automatic image segmentation. It highlights two studies that demonstrate how U-Net- and convolutional neural networks-based architectures have i...
IEEE transactions on pattern analysis and machine intelligence
Nov 6, 2024
Interactive segmentation is a crucial research area in medical image analysis aiming to boost the efficiency of costly annotations by incorporating human feedback. This feedback takes the form of clicks, scribbles, or masks and allows for iterative r...
Early detection and treatment of skin cancer are important for patient recovery and survival. Dermoscopy images can help clinicians for timely identification of cancer, but manual diagnosis is time-consuming, costly, and prone to human error. To cond...
Biomedical physics & engineering express
Nov 6, 2024
This research presents an integrated framework designed to automate the classification of pulmonary chest x-ray images. Leveraging convolutional neural networks (CNNs) with a focus on transformer architectures, the aim is to improve both the accuracy...
BACKGROUND: Intestinal parasitic infections are still a serious public health problem in developing countries, and the diagnosis of parasitic infections requires the first step of parasite/egg detection of samples. Automated detection can eliminate t...
IEEE journal of biomedical and health informatics
Nov 6, 2024
Multi-parametric magnetic resonance imaging (mpMRI) exams have various series types acquired with different imaging protocols. The DICOM headers of these series often have incorrect information due to the sheer diversity of protocols and occasional t...
IEEE journal of biomedical and health informatics
Nov 6, 2024
Multi-modality image registration is an important task in medical imaging because it allows for information from different domains to be correlated. Histopathology plays a crucial role in oncologic surgery as it is the gold standard for investigating...
IEEE journal of biomedical and health informatics
Nov 6, 2024
Automated retinal vessel segmentation is crucial for computer-aided clinical diagnosis and retinopathy screening. However, deep learning faces challenges in extracting complex intertwined structures and subtle small vessels from densely vascularized ...
IEEE journal of biomedical and health informatics
Nov 6, 2024
Recently, federated learning has become a powerful technique for medical image classification due to its ability to utilize datasets from multiple clinical clients while satisfying privacy constraints. However, there are still some obstacles in feder...
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