Gliomas are diffuse, invasive brain tumors. We propose a 3D classification-based diffusion model, cdm, that predicts how a glioma will grow at a voxel-level, on the basis of features specific to the patient, properties of the tumor, and attributes of that voxel. We use Supervised Learning algorithms to learn this general model, by observing the growth patterns of gliomas from other patients. Ou...

This paper applies a hidden Markov model to the problem of Attention Deficit Hyperactivity Disorder (ADHD) diagnosis from resting-state functional Magnetic Resonance Image (fMRI) scans of subjects. The proposed model considers the temporal evolution of fMRI voxel activations in the cortex, cingulate gyrus, and thalamus regions of the brain in order to make a diagnosis. Four feature dimensionali...

A method for predicting the solidification and stress of a digital light processing 3D print process is presented, using voxel-based, multi-layer model to predict degree polymerization material at every stage during print.

Parameter estimation in functional imaging provides unique quantitative measures in clinical diagnosis, and in the evaluation of treatment response and new drugs. Voxel-by-voxel parameter estimations can construct parametric images which visualize the spatial distribution of functional parameters. The low signal-to-noise ratio in single photon emission computed tomography (SPECT) may cause phys...

In radiation treatment (RT) planning, clinicians must trace the outline of a few critical structures on a large number of images. Using automated image segmentation could save tremendous time and effort. Segmentation of the organs near the pubic bone (prostate and bladder) is an important and challenging task: Some of the neighboring organs have similar density values in the CT images and the b...

In this paper, we present a method for 3D volumetric reconstruction of landscape from airborne laser scanner data. The method applies a voxel model, where volume is divided to sub-volume particles, voxels, associated with a scalar or vector value. In the presented study the voxel model is generated from airborne laser scanner data, which enables measurement of large areas. Laser scanning provid...

In computed tomography, the reconstruction is typically obtained on a voxel grid. this work, however, we propose mesh-based method. For tomographic problems, 3D meshes have mostly been studied to simulate data acquisition, but not for reconstruction, which mesh means inverse process of estimating shapes from projections. paper, differentiable forward model that bridge gap between surfaces and o...

Recent advances on 3D object detection heavily rely how the data are represented, i.e., voxel-based or point-based representation. Many existing high performance detectors because this structure can better retain precise point positions. Nevertheless, point-level features lead to computation overheads due unordered storage. In contrast, is suited for feature extraction but often yields lower ac...

Diffusion tensor imaging (DTI) is widely used to characterize tissue micro-architecture and brain connectivity. Yet, DTI suffers serious limitations in regions of crossing fibers because traditional tensor techniques cannot represent multiple, independent intra-voxel orientations. Compressed sensing has been proposed to resolve crossing fibers using a tensor mixture model (e.g., Crossing Fiber ...