AIMC Topic: Algorithms

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Portable Ultrasound Bladder Volume Measurement Over Entire Volume Range Using a Deep Learning Artificial Intelligence Model in a Selected Cohort: A Proof of Principle Study.

Neurourology and urodynamics
OBJECTIVE: We aimed to prospectively investigate whether bladder volume measured using deep learning artificial intelligence (AI) algorithms (AI-BV) is more accurate than that measured using conventional methods (C-BV) if using a portable ultrasound ...

Multi-positive contrastive learning-based cross-attention model for T cell receptor-antigen binding prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: T cells play a vital role in the immune system by recognizing and eliminating infected or cancerous cells, thus driving adaptive immune responses. Their activation is triggered by the binding of T cell receptors (TCRs) to ep...

Automated Microbubble Discrimination in Ultrasound Localization Microscopy by Vision Transformer.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Ultrasound localization microscopy (ULM) has revolutionized microvascular imaging by breaking the acoustic diffraction limit. However, different ULM workflows depend heavily on distinct prior knowledge, such as the impulse response and empirical sele...

A myocardial reorientation method based on feature point detection for quantitative analysis of PET myocardial perfusion imaging.

Computer methods and programs in biomedicine
OBJECTIVE: Reorienting cardiac positron emission tomography (PET) images to the transaxial plane is essential for cardiac PET image analysis. This study aims to design a convolutional neural network (CNN) for automatic reorientation and evaluate its ...

UltrasOM: A mamba-based network for 3D freehand ultrasound reconstruction using optical flow.

Computer methods and programs in biomedicine
BACKGROUND: Three-dimensional (3D) ultrasound (US) reconstruction is of significant value in clinical diagnosis, characterized by its safety, portability, low cost, and high real-time capabilities. 3D freehand ultrasound reconstruction aims to elimin...

A novel approach for ECG signal classification using sliding Euclidean quantization and bitwise pattern encoding.

Computer methods in biomechanics and biomedical engineering
This study aims to introduce a novel, computationally lightweight feature extraction technique called Sliding Euclidean Pattern Quantization (SEPQ), which encodes local morphological patterns of ECG signals using Euclidean distance-based binary repre...

Development of a deep learning method for phase retrieval image enhancement in phase contrast microcomputed tomography.

Journal of microscopy
Propagation-based imaging (one method of X-ray phase contrast imaging) with microcomputed tomography (PBI-µCT) offers the potential to visualise low-density materials, such as soft tissues and hydrogel constructs, which are difficult to be identified...

AI-driven glomerular morphology quantification: a novel pipeline for assessing basement membrane thickness and podocyte foot process effacement in kidney diseases.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Measuring the thickness of the glomerular basement membrane (GBM) and assessing the percentage of podocyte foot process effacement (%PFPE) are important for diagnosing non-neoplastic kidney diseases. However, when performed ...

Algorithmic approaches in hand imaging for rheumatic musculoskeletal diseases: A systematic literature review.

Seminars in arthritis and rheumatism
OBJECTIVE: This systematic literature review provides a comprehensive overview of the use of machine learning (ML) in hand imaging of rheumatic musculoskeletal diseases (RMDs). The review evaluates ML algorithms, imaging modalities, patient populatio...

A systematic review of AI as a digital twin for prostate cancer care.

Computer methods and programs in biomedicine
Artificial Intelligence (AI) and Digital Twin (DT) technologies are rapidly transforming healthcare, offering the potential for personalized, accurate, and efficient medical care. This systematic review focuses on the intersection of AI-based digital...