AIMC Topic: Image Processing, Computer-Assisted

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Pseudo progression identification of glioblastoma with dictionary learning.

Computers in biology and medicine
OBJECTIVE: Although the use of temozolomide in chemoradiotherapy is effective, the challenging clinical problem of pseudo progression has been raised in brain tumor treatment. This study aims to distinguish pseudo progression from true progression.

Automated assessment of thigh composition using machine learning for Dixon magnetic resonance images.

Magma (New York, N.Y.)
OBJECTIVES: To develop and validate a machine learning based automated segmentation method that jointly analyzes the four contrasts provided by Dixon MRI technique for improved thigh composition segmentation accuracy.

Automatic Segmentation of MR Brain Images With a Convolutional Neural Network.

IEEE transactions on medical imaging
Automatic segmentation in MR brain images is important for quantitative analysis in large-scale studies with images acquired at all ages. This paper presents a method for the automatic segmentation of MR brain images into a number of tissue classes u...

Nuquantus: Machine learning software for the characterization and quantification of cell nuclei in complex immunofluorescent tissue images.

Scientific reports
Determination of fundamental mechanisms of disease often hinges on histopathology visualization and quantitative image analysis. Currently, the analysis of multi-channel fluorescence tissue images is primarily achieved by manual measurements of tissu...

Supervised domain adaptation of decision forests: Transfer of models trained in vitro for in vivo intravascular ultrasound tissue characterization.

Medical image analysis
In this paper, we propose a supervised domain adaptation (DA) framework for adapting decision forests in the presence of distribution shift between training (source) and testing (target) domains, given few labeled examples. We introduce a novel metho...

Super-Thresholding: Supervised Thresholding of Protein Crystal Images.

IEEE/ACM transactions on computational biology and bioinformatics
In general, a single thresholding technique is developed or enhanced to separate foreground objects from background for a domain of images. This idea may not generate satisfactory results for all images in a dataset, since different images may requir...

Marginal Space Deep Learning: Efficient Architecture for Volumetric Image Parsing.

IEEE transactions on medical imaging
Robust and fast solutions for anatomical object detection and segmentation support the entire clinical workflow from diagnosis, patient stratification, therapy planning, intervention and follow-up. Current state-of-the-art techniques for parsing volu...

Vision-based Nano Robotic System for High-throughput Non-embedded Cell Cutting.

Scientific reports
Cell cutting is a significant task in biology study, but the highly productive non-embedded cell cutting is still a big challenge for current techniques. This paper proposes a vision-based nano robotic system and then realizes automatic non-embedded ...

Automated discrimination of dicentric and monocentric chromosomes by machine learning-based image processing.

Microscopy research and technique
Dose from radiation exposure can be estimated from dicentric chromosome (DC) frequencies in metaphase cells of peripheral blood lymphocytes. We automated DC detection by extracting features in Giemsa-stained metaphase chromosome images and classifyin...

A Novel Brain Network Construction Method for Exploring Age-Related Functional Reorganization.

Computational intelligence and neuroscience
The human brain undergoes complex reorganization and changes during aging. Using graph theory, scientists can find differences in topological properties of functional brain networks between young and elderly adults. However, these differences are som...