AIMC Topic: Anisotropy

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Two-Dimensional Light Scattering Anisotropy Cytometry for Label-Free Classification of Ovarian Cancer Cells via Machine Learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
We develop a single-mode fiber-based cytometer for the obtaining of two-dimensional (2D) light scattering patterns from static single cells. Anisotropy of the 2D light scattering patterns of single cells from ovarian cancer and normal cell lines is i...

3D APA-Net: 3D Adversarial Pyramid Anisotropic Convolutional Network for Prostate Segmentation in MR Images.

IEEE transactions on medical imaging
Accurate and reliable segmentation of the prostate gland using magnetic resonance (MR) imaging has critical importance for the diagnosis and treatment of prostate diseases, especially prostate cancer. Although many automated segmentation approaches, ...

Classification and Recognition of Ovarian Cells Based on Two-Dimensional Light Scattering Technology.

Journal of medical systems
Ovarian cancer is a very insidious malignant tumor. In order to detect ovarian cancer cells early, the classification and recognition of ovarian cancer cells is mainly studied by two-dimensional light scattering technology. Firstly, a single-cell two...

A deep learning approach to estimation of subject-level bias and variance in high angular resolution diffusion imaging.

Magnetic resonance imaging
The ability to evaluate empirical diffusion MRI acquisitions for quality and to correct the resulting imaging metrics allows for improved inference and increased replicability. Previous work has shown promise for estimation of bias and variance of ge...

Application of a machine learning method to whole brain white matter injury after radiotherapy for nasopharyngeal carcinoma.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: The purpose/aim of this study was to 1) use magnetic resonance diffusion tensor imaging (DTI), fibre bundle/tract-based spatial statistics (TBSS) and machine learning methods to study changes in the white matter (WM) structure and whole b...

Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging.

European radiology
OBJECTIVES: Preoperative, noninvasive prediction of the meningioma grade is important because it influences the treatment strategy. The purpose of this study was to evaluate the role of radiomics features of postcontrast T1-weighted images (T1C), app...

Simultaneous NODDI and GFA parameter map generation from subsampled q-space imaging using deep learning.

Magnetic resonance in medicine
PURPOSE: To develop a robust multidimensional deep-learning based method to simultaneously generate accurate neurite orientation dispersion and density imaging (NODDI) and generalized fractional anisotropy (GFA) parameter maps from undersampled q-spa...

Predicting chemo-brain in breast cancer survivors using multiple MRI features and machine-learning.

Magnetic resonance in medicine
PURPOSE: Breast cancer (BC) is the most common cancer in women worldwide. There exist various advanced chemotherapy drugs for BC; however, chemotherapy drugs may result in brain damage during treatment. When a patient's brain is changed in response t...

Individualized prediction of dispositional worry using white matter connectivity.

Psychological medicine
BACKGROUND: Excessive worry is a defining feature of generalized anxiety disorder and is present in a wide range of other psychiatric conditions. Therefore, individualized predictions of worry propensity could be highly relevant in clinical practice,...

Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics.

Medical & biological engineering & computing
Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reacti...