AIMC Topic: Image Processing, Computer-Assisted

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Exploiting Global Structure Information to Improve Medical Image Segmentation.

Sensors (Basel, Switzerland)
In this paper, we propose a method to enhance the performance of segmentation models for medical images. The method is based on convolutional neural networks that learn the global structure information, which corresponds to anatomical structures in m...

A combined microfluidic deep learning approach for lung cancer cell high throughput screening toward automatic cancer screening applications.

Scientific reports
Lung cancer is a leading cause of cancer death in both men and women worldwide. The high mortality rate in lung cancer is in part due to late-stage diagnostics as well as spread of cancer-cells to organs and tissues by metastasis. Automated lung canc...

Deep learning-enhanced light-field imaging with continuous validation.

Nature methods
Visualizing dynamic processes over large, three-dimensional fields of view at high speed is essential for many applications in the life sciences. Light-field microscopy (LFM) has emerged as a tool for fast volumetric image acquisition, but its effect...

A feature fusion deep-projection convolution neural network for vehicle detection in aerial images.

PloS one
With the rapid development of Unmanned Aerial Vehicles, vehicle detection in aerial images plays an important role in different applications. Comparing with general object detection problems, vehicle detection in aerial images is still a challenging ...

Quantification of Blood Flow Velocity in the Human Conjunctival Microvessels Using Deep Learning-Based Stabilization Algorithm.

Sensors (Basel, Switzerland)
The quantification of blood flow velocity in the human conjunctiva is clinically essential for assessing microvascular hemodynamics. Since the conjunctival microvessel is imaged in several seconds, eye motion during image acquisition causes motion ar...

Deep learning methods allow fully automated segmentation of metacarpal bones to quantify volumetric bone mineral density.

Scientific reports
Arthritis patients develop hand bone loss, which leads to destruction and functional impairment of the affected joints. High resolution peripheral quantitative computed tomography (HR-pQCT) allows the quantification of volumetric bone mineral density...

Chronic cholestasis detection by a novel tool: automated analysis of cytokeratin 7-stained liver specimens.

Diagnostic pathology
BACKGROUND: The objective was to build a novel method for automated image analysis to locate and quantify the number of cytokeratin 7 (K7)-positive hepatocytes reflecting cholestasis by applying deep learning neural networks (AI model) in a cohort of...

Improving phase-based conductivity reconstruction by means of deep learning-based denoising of phase data for 3T MRI.

Magnetic resonance in medicine
PURPOSE: To denoise phase using a deep learning method for phase-based in vivo electrical conductivity reconstruction in a 3T MR system.

Evaluation of an open-source machine-learning tool to quantify bone marrow plasma cells.

Journal of clinical pathology
AIMS: The objective of this study was to develop and validate an open-source digital pathology tool, QuPath, to automatically quantify CD138-positive bone marrow plasma cells (BMPCs).

Multiscale attention guided U-Net architecture for cardiac segmentation in short-axis MRI images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automatic cardiac segmentation plays an utmost role in the diagnosis and quantification of cardiovascular diseases.