AIMC Topic: Image Processing, Computer-Assisted

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Two stage residual CNN for texture denoising and structure enhancement on low dose CT image.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: X-ray computed tomography (CT) plays an important role in modern medical science. Human health problems caused by CT radiation have attracted the attention of the academic community widely. Reducing radiation dose results in...

Ovarian Toxicity Assessment in Histopathological Images Using Deep Learning.

Toxicologic pathology
As ovarian toxicity is often a safety concern for cancer therapeutics, identification of ovarian pathology is important in early stages of preclinical drug development, particularly when the intended patient population include women of child-bearing ...

Generic Isolated Cell Image Generator.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Building automated cancer screening systems based on image analysis is currently a hot topic in computer vision and medical imaging community. One of the biggest challenges of such systems, especially those using state-of-the-art deep learning techni...

Development of a real-time endoscopic image diagnosis support system using deep learning technology in colonoscopy.

Scientific reports
Gaps in colonoscopy skills among endoscopists, primarily due to experience, have been identified, and solutions are critically needed. Hence, the development of a real-time robust detection system for colorectal neoplasms is considered to significant...

CR-Unet: A Composite Network for Ovary and Follicle Segmentation in Ultrasound Images.

IEEE journal of biomedical and health informatics
Transvaginal ultrasound (TVUS) is widely used in infertility treatment. The size and shape of the ovary and follicles must be measured manually for assessing their physiological status by sonographers. However, this process is extremely time-consumin...

DeepBranch: Deep Neural Networks for Branch Point Detection in Biomedical Images.

IEEE transactions on medical imaging
Morphology reconstruction of tree-like structures in volumetric images, such as neurons, retinal blood vessels, and bronchi, is of fundamental interest for biomedical research. 3D branch points play an important role in many reconstruction applicatio...

Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs.

Nature methods
Cryo-electron microscopy is a popular method for the determination of protein structures; however, identifying a sufficient number of particles for analysis can take months of manual effort. Current computational approaches find many false positives ...

Democratized image analytics by visual programming through integration of deep models and small-scale machine learning.

Nature communications
Analysis of biomedical images requires computational expertize that are uncommon among biomedical scientists. Deep learning approaches for image analysis provide an opportunity to develop user-friendly tools for exploratory data analysis. Here, we us...

Independent brain F-FDG PET attenuation correction using a deep learning approach with Generative Adversarial Networks.

Hellenic journal of nuclear medicine
OBJECTIVE: Attenuation correction (AC) of positron emission tomography (PET) data poses a challenge when no transmission data or computed tomography (CT) data are available, e.g. in stand alone PET scanners or PET/magnetic resonance imaging (MRI). In...