AIMC Topic: Image Processing, Computer-Assisted

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Deep learning for fast denoising filtering in ultrasound localization microscopy.

Physics in medicine and biology
Addition of a denoising filter step in ultrasound localization microscopy (ULM) has been shown to effectively reduce the error localizations of microbubbles (MBs) and achieve resolution improvement for super-resolution ultrasound (SR-US) imaging. How...

A Structure-Aware Hierarchical Graph-Based Multiple Instance Learning Framework for pT Staging in Histopathological Image.

IEEE transactions on medical imaging
Pathological primary tumor (pT) stage focuses on the infiltration degree of the primary tumor to surrounding tissues, which relates to the prognosis and treatment choices. The pT staging relies on the field-of-views from multiple magnifications in th...

Physics-Guided Deep Scatter Estimation by Weak Supervision for Quantitative SPECT.

IEEE transactions on medical imaging
Accurate scatter estimation is important in quantitative SPECT for improving image contrast and accuracy. With a large number of photon histories, Monte-Carlo (MC) simulation can yield accurate scatter estimation, but is computationally expensive. Re...

Min-Max Similarity: A Contrastive Semi-Supervised Deep Learning Network for Surgical Tools Segmentation.

IEEE transactions on medical imaging
A common problem with segmentation of medical images using neural networks is the difficulty to obtain a significant number of pixel-level annotated data for training. To address this issue, we proposed a semi-supervised segmentation network based on...

Anatomy segmentation in laparoscopic surgery: comparison of machine learning and human expertise - an experimental study.

International journal of surgery (London, England)
BACKGROUND: Lack of anatomy recognition represents a clinically relevant risk in abdominal surgery. Machine learning (ML) methods can help identify visible patterns and risk structures; however, their practical value remains largely unclear.

Approaches and Limitations of Machine Learning for Synthetic Ultrasound Generation: A Scoping Review.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
This scoping review examines the emerging field of synthetic ultrasound generation using machine learning (ML) models in radiology. Nineteen studies were analyzed, revealing three primary methodological strategies: unconditional generation, condition...

Deep learning imaging reconstruction of reduced-dose 40 keV virtual monoenergetic imaging for early detection of colorectal cancer liver metastases.

European journal of radiology
OBJECTIVE: To explore whether reduced-dose (RD) gemstone spectral imaging (GSI) and deep learning image reconstruction (DLIR) of 40 keV virtual monoenergetic image (VMI) enhanced the early detection and diagnosis of colorectal cancer liver metastases...

Developing tongue coating status assessment using image recognition with deep learning.

Journal of prosthodontic research
PURPOSE: To build an image recognition network to evaluate tongue coating status.

An automatic progressive chromosome segmentation approach using deep learning with traditional image processing.

Medical & biological engineering & computing
The fully automatic chromosome analysis system plays an important role in the detection of genetic diseases, which in turn can reduce the diagnosis burden for cytogenetic experts. Chromosome segmentation is a critical step for such a system. However,...

PC-Reg: A pyramidal prediction-correction approach for large deformation image registration.

Medical image analysis
Deformable image registration plays an important role in medical image analysis. Deep neural networks such as VoxelMorph and TransMorph are fast, but limited to small deformations and face challenges in the presence of large deformations. To tackle l...