AIMC Topic: Imaging, Three-Dimensional

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Dendritic spine classification using shape and appearance features based on two-photon microscopy.

Journal of neuroscience methods
BACKGROUND: Neuronal morphology and function are highly coupled. In particular, dendritic spine morphology is strongly governed by the incoming neuronal activity. The first step towards understanding the structure-function relationships is to classif...

Online 3D Ear Recognition by Combining Global and Local Features.

PloS one
The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for onl...

Integrating Online and Offline Three-Dimensional Deep Learning for Automated Polyp Detection in Colonoscopy Videos.

IEEE journal of biomedical and health informatics
Automated polyp detection in colonoscopy videos has been demonstrated to be a promising way for colorectal cancer prevention and diagnosis. Traditional manual screening is time consuming, operator dependent, and error prone; hence, automated detectio...

Artificial Neural Networks as a powerful numerical tool to classify specific features of a tooth based on 3D scan data.

Computers in biology and medicine
Chairside manufacturing based on digital image acquisition is gainingincreasing importance in dentistry. For the standardized application of these methods, it is paramount to have highly automated digital workflows that can process acquired 3D image ...

Automated quantification of three-dimensional organization of fiber-like structures in biological tissues.

Biomaterials
Fiber-like structures are prevalent in biological tissues, yet quantitative approaches to assess their three-dimensional (3D) organization are lacking. We develop 3D directional variance, as a quantitative biomarker of truly 3D fibrillar organization...

Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.

International journal of computer assisted radiology and surgery
PURPOSE: Multi-organ segmentation from CT images is an essential step for computer-aided diagnosis and surgery planning. However, manual delineation of the organs by radiologists is tedious, time-consuming and poorly reproducible. Therefore, we propo...

Automatic 3D liver segmentation based on deep learning and globally optimized surface evolution.

Physics in medicine and biology
The detection and delineation of the liver from abdominal 3D computed tomography (CT) images are fundamental tasks in computer-assisted liver surgery planning. However, automatic and accurate segmentation, especially liver detection, remains challeng...

First report of robot-assisted transperineal fusion versus off-target biopsy in patients undergoing repeat prostate biopsy.

World journal of urology
PURPOSE: To clarify the value of targeted versus off-target biopsies in men with a suspicion of prostate cancer (PC) and a visible lesion in multi-parametric magnetic resonance imaging (mpMRI) using transperineal robot-assisted biopsy.

Automatic segmentation of airway tree based on local intensity filter and machine learning technique in 3D chest CT volume.

International journal of computer assisted radiology and surgery
PURPOSE: Airway segmentation plays an important role in analyzing chest computed tomography (CT) volumes for computerized lung cancer detection, emphysema diagnosis and pre- and intra-operative bronchoscope navigation. However, obtaining a complete 3...

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine.

Journal of visualized experiments : JoVE
Proprioceptive drift, which is a perceptual shift in body-part position from the unseen real body to a visible body-like image, has been measured as the behavioral correlate for the sense of ownership. Previously, the estimation of proprioceptive dri...