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Convolutional Neural Networks (CNNs) have been recently employed to solve problems from both the computer vision and medical image analysis fields. Despite their popularity, most approaches are only able to process 2D images while most medical data used in clinical practice consists of 3D volumes. In this work we propose an approach to 3D image segmentation based on a volumetric, fully convolutional,...
The paper addresses a problem of feature selection for automatic prostate segmentation in Computed Tomography (CT) planning data for radiotherapy process. The following image descriptors have been tested in 2D and 3D scenarios: standard Hounsfield Unit (HU) profiles, histogram of oriented gradient (HoG), Haar wavelets, and Modality Independent Neighborhood Descriptor (MIND). The task was to distinguish...
Tumor cellularity, the number of cells in the tumor, is an important tissue microstructural feature, which is useful for cancer diagnosis and cell number related treatment. Histopathological examination of tissues reveals the tissue microstructure hence permits to investigate cellularity, but is usually available only as a small sample or after resection. Diffusion-weighted MRI (DWI) is a non-invasive...
We present a method for collaborative augmented reality (AR) that enables users from different viewpoints to interpret object references specified via 2D on-screen circling gestures. Based on a user's 2D drawing annotation, the method segments out the userselected object using an incomplete or imperfect scene model and the color image from the drawing viewpoint. Specifically, we propose a novel segmentation...
Characterizing the microvascular architecture has a wide range of medical and biological applications in the fields of angiology, oncology and dermatology. We propose a method to segment vessels in 2D temporal sequences and in 3D images using high-frequency ultrasound (25–50 MHz). The method takes as input the native ultrasound images, and detects the vessels based the intensity and the dynamical...
We develop an unsupervised graph clustering and image segmentation algorithm based on non-negative matrix factorization. We consider arbitrarily represented visual signals (in 2D or 3D) and use a graph embedding approach for image or point cloud segmentation. We extend a Projective Non-negative Matrix Factorization variant to include local spatial relationships over the image graph. By using properly...
Given the widespread availability of point cloud data from consumer depth sensors, 3D point cloud segmentation becomes a promising building block for high level applications such as scene understanding and interaction analysis. It benefits from the richer information contained in real world 3D data compared to 2D images. This also implies that the classical color segmentation challenges have shifted...
The Mitral Valve is a structure on the left side of the human heart that regulates the flow of oxygenated blood into the Left Ventricle and also helps maintain the pressure within the Left Ventricle when the blood gets pumped to the rest of the body from the Left Ventricle. Pathology of the Mitral Valve often manifests through structural changes in the anatomy. Assessment of Mitral Valve pathology...
Estimation of tooth axis is needed for some clinical dental treatment. Existing methods require to segment the tooth volume from Computed Tomography (CT) images, and then estimate the axis from the tooth volume. However, they may fail during estimating molar axis due to that the tooth segmentation from CT images is challenging and current segmentation methods may get poor segmentation results especially...
The intensity of the light observed from every position and direction in a real scene can be modeled as a highdimensional field, namely the plenoptic function. This field codes the radiance information as a function of space, orientation, wavelength, and time. In the scope of depth estimation, several strategies have been developed to obtain a representation of the spatial structure of a scene. However,...
In this paper, the implementation to estimate the focus map spatially based on the intentional reblur of one image, which is the only input data, is presented. This enables flexible computation in the spatial domain, rather than the frequency domain. The gradient magnitude term widely used in image processing was used to derive a ratio map. The pixels closer to the focal point of the camera were on...
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