AI Medical Compendium Topic

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Image Interpretation, Computer-Assisted

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Deep Interactive Segmentation of Medical Images: A Systematic Review and Taxonomy.

IEEE transactions on pattern analysis and machine intelligence
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...

TPAFNet: Transformer-Driven Pyramid Attention Fusion Network for 3D Medical Image Segmentation.

IEEE journal of biomedical and health informatics
The field of 3D medical image segmentation is witnessing a growing trend in the utilization of combined networks that integrate convolutional neural networks and transformers. Nevertheless, prevailing hybrid networks are confronted with limitations i...

Classification of Multi-Parametric Body MRI Series Using Deep Learning.

IEEE journal of biomedical and health informatics
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...

Framework for Deep Learning Based Multi-Modality Image Registration of Snapshot and Pathology Images.

IEEE journal of biomedical and health informatics
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...

GKE-TUNet: Geometry-Knowledge Embedded TransUNet Model for Retinal Vessel Segmentation Considering Anatomical Topology.

IEEE journal of biomedical and health informatics
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 ...

Multi-Loss Disentangled Generative-Discriminative Learning for Multimodal Representation in Schizophrenia.

IEEE journal of biomedical and health informatics
Schizophrenia (SCZ) is a multifactorial mental illness, thus it will be beneficial for exploring this disease using multimodal data, including functional magnetic resonance imaging (fMRI), genes, and the gut microbiome. Previous studies reported comb...

Specificity-Aware Federated Learning With Dynamic Feature Fusion Network for Imbalanced Medical Image Classification.

IEEE journal of biomedical and health informatics
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...

Minimizing prostate diffusion weighted MRI examination time through deep learning reconstruction.

Clinical imaging
PURPOSE: To study the diagnostic image quality of high b-value diffusion weighted images (DWI) derived from standard and variably reduced datasets reconstructed with a commercially available deep learning reconstruction (DLR) algorithm.

Multi-lesion segmentation guided deep attention network for automated detection of diabetic retinopathy.

Computers in biology and medicine
Accurate multi-lesion segmentation together with automated grading on fundus images played a vital role in diagnosing and treating diabetic retinopathy (DR). Nevertheless, the intrinsic patterns of fundus lesions aggravated challenges in DR detection...