AIMC Topic: Image Processing, Computer-Assisted

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Computer vision techniques for high-speed atomic force microscopy of DNA molecules.

Nanotechnology
High-speed atomic force microscopy (HSAFM) can produce thousands of topographic, nanoscale images over a small area. One emerging application of this technique is the detection and sizing of single DNA molecules derived from biological experiments an...

Dose-aware denoising diffusion model for low-dose CT.

Physics in medicine and biology
Low-dose computed tomography (LDCT) denoising plays an important role in medical imaging for reducing the radiation dose to patients. Recently, various data-driven and diffusion-based deep learning (DL) methods have been developed and shown promising...

Deep learning-based contour propagation in magnetic resonance imaging-guided radiotherapy of lung cancer patients.

Physics in medicine and biology
Fast and accurate organ-at-risk (OAR) and gross tumor volume (GTV) contour propagation methods are needed to improve the efficiency of magnetic resonance (MR) imaging-guided radiotherapy. We trained deformable image registration networks to accuratel...

DCSLK: Combined large kernel shared convolutional model with dynamic channel Sampling.

NeuroImage
This study centers around the competition between Convolutional Neural Networks (CNNs) with large convolutional kernels and Vision Transformers in the domain of computer vision, delving deeply into the issues pertaining to parameters and computationa...

A robust automated segmentation method for white matter hyperintensity of vascular-origin.

NeuroImage
White matter hyperintensity (WMH) is a primary manifestation of small vessel disease (SVD), leading to vascular cognitive impairment and other disorders. Accurate WMH quantification is vital for diagnosis and prognosis, but current automatic segmenta...

Characterizing DNA Origami Nanostructures in TEM Images Using Convolutional Neural Networks.

Journal of chemical information and modeling
Artificial intelligence (AI) models remain an emerging strategy to accelerate materials design and development. We demonstrate that CNN models can characterize DNA origami nanostructures employed in programmable self-assembly, which is important in m...

Optimization-based image reconstruction regularized with inter-spectral structural similarity for limited-angle dual-energy cone-beam CT.

Physics in medicine and biology
. Limited-angle dual-energy (DE) cone-beam CT (CBCT) is considered as a potential solution to achieve fast and low-dose DE imaging on current CBCT scanners without hardware modification. However, its clinical implementations are hindered by the chall...

Deep learning generalization study on optical coherence tomography image denoising.

Physics in medicine and biology
Noise is a key factor determining imaging quality for optical coherence tomography (OCT). Although deep learning has emerged as an effective denoising method, its generalization capability remains limited, especially when test noise levels deviate fr...

Photon-counting micro-CT scanner for deep learning-enabled small animal perfusion imaging.

Physics in medicine and biology
In this work, we introduce a benchtop, turn-table photon-counting (PC) micro-computed tomography (CT) scanner and highlight its application for dynamic small animal perfusion imaging.Built on recently published hardware, the system now features a CdT...

Recent advancements in feature extraction and classification based bone cancer detection - a systematic review.

Biomedical physics & engineering express
Cancer is a deadly disease that occurs due to the uncontrolled growth of abnormal cells. Bone cancer is the third most occurring disease; approximately 10,000 patients suffer from bone cancer in India annually. It can lead to death if not diagnosed i...