AIMC Topic: Image Processing, Computer-Assisted

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Medical Instrument Segmentation in 3D US by Hybrid Constrained Semi-Supervised Learning.

IEEE journal of biomedical and health informatics
Medical instrument segmentation in 3D ultrasound is essential for image-guided intervention. However, to train a successful deep neural network for instrument segmentation, a large number of labeled images are required, which is expensive and time-co...

A data-driven deep learning pipeline for quantitative susceptibility mapping (QSM).

Magnetic resonance imaging
PURPOSE: This study developed a data-driven optimization to improve the accuracy of deep learning QSM quantification.

FastSurferVINN: Building resolution-independence into deep learning segmentation methods-A solution for HighRes brain MRI.

NeuroImage
Leading neuroimaging studies have pushed 3T MRI acquisition resolutions below 1.0 mm for improved structure definition and morphometry. Yet, only few, time-intensive automated image analysis pipelines have been validated for high-resolution (HiRes) s...

Quantitative features to assist in the diagnostic assessment of chronic lymphocytic leukemia progression.

The Journal of pathology
The use of artificial intelligence methods in the image-based diagnostic assessment of hematological diseases is a growing trend in recent years. In these methods, the selection of quantitative features that describe cytological characteristics plays...

Semantic Object Accuracy for Generative Text-to-Image Synthesis.

IEEE transactions on pattern analysis and machine intelligence
Generative adversarial networks conditioned on textual image descriptions are capable of generating realistic-looking images. However, current methods still struggle to generate images based on complex image captions from a heterogeneous domain. Furt...

A Novel Encoding and Decoding Calibration Guiding Pathway for Pathological Image Analysis.

IEEE/ACM transactions on computational biology and bioinformatics
Diagnostic pathology is the foundation and gold standard for identifying carcinomas, and the accurate quantification of pathological images can provide objective clues for pathologists to make more convincing diagnosis. Recently, the encoder-decoder ...

Automated segmentation of magnetic resonance bone marrow signal: a feasibility study.

Pediatric radiology
BACKGROUND: Manual assessment of bone marrow signal is time-consuming and requires meticulous standardisation to secure adequate precision of findings.

Fused Projection-Based Point Cloud Segmentation.

Sensors (Basel, Switzerland)
Semantic segmentation is used to enable a computer to understand its surrounding environment. In image processing, images are partitioned into segments for this purpose. State-of-the-art methods make use of Convolutional Neural Networks to segment a ...

Automated characterisation of microglia in ageing mice using image processing and supervised machine learning algorithms.

Scientific reports
The resident macrophages of the central nervous system, microglia, are becoming increasingly implicated as active participants in neuropathology and ageing. Their diverse and changeable morphology is tightly linked with functions they perform, enabli...