AIMC Topic: Molecular Imaging
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Imaging Beyond Seeing: Early Prognosis of Cancer Treatment.
Small methods
Dec 18, 2020
Assessing cancer response to therapeutic interventions has been realized as an important course to early predict curative efficacy and treatment outcomes due to tumor heterogeneity. Compared to the traditional invasive tissue biopsy method, molecular...
Deep convolution neural networks based artifact suppression in under-sampled radial acquisitions of myocardial T mapping images.
Physics in medicine and biology
Nov 24, 2020
We developed a deep convolutional neural network (CNN) based method to remove streaking artefact from accelerated radial acquisitions of myocardial T -mapping images. A deep CNN based on a modified U-Net architecture was developed and trained to remo...
Automatic discovery of clinically interpretable imaging biomarkers for Mycobacterium tuberculosis supersusceptibility using deep learning.
EBioMedicine
Nov 7, 2020
BACKGROUND: Identifying which individuals will develop tuberculosis (TB) remains an unresolved problem due to few animal models and computational approaches that effectively address its heterogeneity. To meet these shortcomings, we show that Diversit...
Molecular imaging and deep learning analysis of uMUC1 expression in response to chemotherapy in an orthotopic model of ovarian cancer.
Scientific reports
Sep 10, 2020
Artificial Intelligence (AI) algorithms including deep learning have recently demonstrated remarkable progress in image-recognition tasks. Here, we utilized AI for monitoring the expression of underglycosylated mucin 1 (uMUC1) tumor antigen, a biomar...
Artificial Intelligence Analysis of Magnetic Particle Imaging for Islet Transplantation in a Mouse Model.
Molecular imaging and biology
Aug 24, 2020
PURPOSE: Current approaches to quantification of magnetic particle imaging (MPI) for cell-based therapy are thwarted by the lack of reliable, standardized methods of segmenting the signal from background in images. This calls for the development of a...
Artificial intelligence and radiomics in pediatric molecular imaging.
Methods (San Diego, Calif.)
Jun 13, 2020
In the past decade, a new approach for quantitative analysis of medical images and prognostic modelling has emerged. Defined as the extraction and analysis of a large number of quantitative parameters from medical images, radiomics is an evolving fie...
Discovering the hidden messages within cell trajectories using a deep learning approach for in vitro evaluation of cancer drug treatments.
Scientific reports
May 6, 2020
We describe a novel method to achieve a universal, massive, and fully automated analysis of cell motility behaviours, starting from time-lapse microscopy images. The approach was inspired by the recent successes in application of machine learning for...
Microaneurysms detection in color fundus images using machine learning based on directional local contrast.
Biomedical engineering online
Apr 15, 2020
BACKGROUND: As one of the major complications of diabetes, diabetic retinopathy (DR) is a leading cause of visual impairment and blindness due to delayed diagnosis and intervention. Microaneurysms appear as the earliest symptom of DR. Accurate and re...
Nondestructive Detection of Targeted Microbubbles Using Dual-Mode Data and Deep Learning for Real-Time Ultrasound Molecular Imaging.
IEEE transactions on medical imaging
Apr 9, 2020
Ultrasound molecular imaging (UMI) is enabled by targeted microbubbles (MBs), which are highly reflective ultrasound contrast agents that bind to specific biomarkers. Distinguishing between adherent MBs and background signals can be challenging in vi...
Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine Learning.
International journal of radiation oncology, biology, physics
Jan 23, 2020
PURPOSE: Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Current methods to evaluate breast skin toxicity include clinical examination, visual inspection, and patient-reported symptoms. Physiological changes ass...
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