AIMC Topic: Image Processing, Computer-Assisted

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Artificial Intelligence Based Framework to Quantify the Cardiomyocyte Structural Integrity in Heart Slices.

Cardiovascular engineering and technology
PURPOSE: Drug induced cardiac toxicity is a disruption of the functionality of cardiomyocytes which is highly correlated to the organization of the subcellular structures. We can analyze cellular structures by utilizing microscopy imaging data. Howev...

TGAN: A simple model update strategy for visual tracking via template-guidance attention network.

Neural networks : the official journal of the International Neural Network Society
Visual attention has been widely used in various fields of visual tasks in recent years. Recently, visual trackers based on probabilistic discriminative model prediction (PrDiMP) and Siamese box adaptive network (SiamBAN) have attracted much attentio...

A mechatronics data collection, image processing, and deep learning platform for clinical posture analysis: a technical note.

Physical and engineering sciences in medicine
Static and dynamic posture analysis was a critical clinical examination in physiotherapy and rehabilitation. It was a time-consuming task for clinicians, so a semi-automatic method can facilitate this process as well as provide well-documented medica...

Multi-muscle deep learning segmentation to automate the quantification of muscle fat infiltration in cervical spine conditions.

Scientific reports
Muscle fat infiltration (MFI) has been widely reported across cervical spine disorders. The quantification of MFI requires time-consuming and rater-dependent manual segmentation techniques. A convolutional neural network (CNN) model was trained to se...

Automatic detection of pathological myopia using machine learning.

Scientific reports
Pathological myopia is a severe case of myopia, i.e., nearsightedness. Pathological myopia is also known as degenerative myopia because it ultimately leads to blindness. In pathological myopia, certain myopia-specific pathologies occur at the eye's p...

Deep Convolutional Clustering-Based Time Series Anomaly Detection.

Sensors (Basel, Switzerland)
This paper presents a novel approach for anomaly detection in industrial processes. The system solely relies on unlabeled data and employs a 1D-convolutional neural network-based deep autoencoder architecture. As a core novelty, we split the autoenco...

Dose reduction potential of vendor-agnostic deep learning model in comparison with deep learning-based image reconstruction algorithm on CT: a phantom study.

European radiology
OBJECTIVES: To compare the dose reduction potential (DRP) of a vendor-agnostic deep learning model (DLM, ClariCT.AI) with that of a vendor-specific deep learning-based image reconstruction algorithm (DLR, TrueFidelity™).

TSU-net: Two-stage multi-scale cascade and multi-field fusion U-net for right ventricular segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurate segmentation of the right ventricle from cardiac magnetic resonance images (MRI) is a critical step in cardiac function analysis and disease diagnosis. It is still an open problem due to some difficulties, such as a large variety of object s...

A novel M-SegNet with global attention CNN architecture for automatic segmentation of brain MRI.

Computers in biology and medicine
In this paper, we propose a novel M-SegNet architecture with global attention for the segmentation of brain magnetic resonance imaging (MRI). The proposed architecture consists of a multiscale deep network at the encoder side, deep supervision at the...

Detection of fraud in ginger powder using an automatic sorting system based on image processing technique and deep learning.

Computers in biology and medicine
Ginger is a well-known product in the food and pharmaceutical industries. Ginger is one of the spices which are adulterated for economic gain. The lack of marketability of grade 3 chickpeas (small and broken chickpeas) and their very low price have m...