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Image Interpretation, Computer-Assisted

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Have We Solved Glottis Segmentation? Review and Commentary.

Journal of voice : official journal of the Voice Foundation
Quantification of voice physiology has been a key research goal. Segmenting the glottal area to describe the vocal fold motion has seen increased attention in the last two decades. However, researchers struggled to fully automatize the segmentation t...

Interpretable deep learning architecture for gastrointestinal disease detection: A Tri-stage approach with PCA and XAI.

Computers in biology and medicine
GI abnormalities significantly increase mortality rates and impose considerable strain on healthcare systems, underscoring the essential requirement for rapid detection, precise diagnosis, and efficient strategic treatment. To develop a CAD system, t...

Development and Validation of a Deep Learning System to Differentiate HER2-Zero, HER2-Low, and HER2-Positive Breast Cancer Based on Dynamic Contrast-Enhanced MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Previous studies explored MRI-based radiomic features for differentiating between human epidermal growth factor receptor 2 (HER2)-zero, HER2-low, and HER2-positive breast cancer, but deep learning's effectiveness is uncertain.

Automated Classification of Body MRI Sequences Using Convolutional Neural Networks.

Academic radiology
RATIONALE AND OBJECTIVES: Multi-parametric MRI (mpMRI) studies of the body are routinely acquired in clinical practice. However, a standardized naming convention for MRI protocols and series does not exist currently. Conflicts in the series descripti...

Current status and future directions of explainable artificial intelligence in medical imaging.

European journal of radiology
The inherent "black box" nature of AI algorithms presents a substantial barrier to the widespread adoption of the technology in clinical settings, leading to a lack of trust among users. This review begins by examining the foundational stages involve...

Adaptive Annotation Correlation Based Multi-Annotation Learning for Calibrated Medical Image Segmentation.

IEEE journal of biomedical and health informatics
Medical image segmentation is a fundamental task in many clinical applications, yet current automated segmentation methods rely heavily on manual annotations, which are inherently subjective and prone to annotation bias. Recently, modeling annotator ...

DualStreamFoveaNet: A Dual Stream Fusion Architecture With Anatomical Awareness for Robust Fovea Localization.

IEEE journal of biomedical and health informatics
Accurate fovea localization is essential for analyzing retinal diseases to prevent irreversible vision loss. While current deep learning-based methods outperform traditional ones, they still face challenges such as the lack of local anatomical landma...

Weakly Supervised Classification for Nasopharyngeal Carcinoma With Transformer in Whole Slide Images.

IEEE journal of biomedical and health informatics
Pathological examination of nasopharyngeal carcinoma (NPC) is an indispensable factor for diagnosis, guiding clinical treatment and judging prognosis. Traditional and fully supervised NPC diagnosis algorithms require manual delineation of regions of ...

tDKI-Net: A Joint q-t Space Learning Network for Diffusion-Time-Dependent Kurtosis Imaging.

IEEE journal of biomedical and health informatics
Time-dependent diffusion magnetic resonance imaging (TDDMRI) is useful for the non-invasive characterization of tissue microstructure. These models require densely sampled q-t space data for microstructural fitting, leading to very time-consuming acq...