Search results for "image"

Artificial Neural Network Based Abdominal Organ Segmentations: A Review

2015

There are many neural network based abdominal organ segmentation approaches from medical images. Computed tomography images were mostly used in these approaches. Applied techniques are usually based on prior information regarding position, shape, and size of organs in these methods. In the literature, there are only a few neural network based techniques that were implemented to segment abdominal organs from magnetic resonance based images. In this paper, we present these methods and their results.

Flip-angle measurement by magnetization inversion: Calibration of magnetization nutation angle in hyperpolarized 3 He magnetic resonance imaging lung…

2010

The aim of this work was to establish a new, fast, and robust method of flip-angle calibration for magnetic resonance imaging of hyperpolarized 3He. The method called flip-angle measurement with magnetization inversion is based on acquiring images from periodically inverted longitudinal magnetization created using the spatial modulation of magnetization technique. By measuring the width of the area where the magnetization was inverted by the spatial modulation of magnetization preparation in phase images, the flip angle can be generated using a simple equation. To validate and establish the limits of the proposed method, flip-angle measurement with magnetization inversion acquisitions were …

Editorial: Breakthrough BCI Applications in Medicine

2020

A fourier-based algorithm for micro-calcification enhancement in mammographic images

2008

Breast cancer is the most widespread cancer in women in the world; it manifests mostly in two forms: microcalcifications and massive lesions. These two forms differ in density, size, shape and number. Consequently, there are two different kinds of mammographic CAD algorithms: those for microcalcifications detection, and those for massive lesions detection. The microcalcifications detection is a hard task, since they are quite small and often poorly contrasted against the background, especially in images affected by digitization noise. In a CAD system the ROI Hunter plays an important role, because missed microcalcifications at this level are definitely lost. For this reason, highlighting me…

Beyond the word and image: III. Neurodynamic properties of the semantic network

2019

AbstractUnderstanding the neural process underlying the comprehension of visual images and sentences remains a major open challenge in cognitive neuroscience. We previously demonstrated with fMRI and DTI that comprehension of visual images and sentences describing human activities recruits a common semantic system. The current research tests the hypothesis that this common semantic system will display similar neural dynamics during processing in these two modalities. To investigate these neural dynamics we recorded EEG from naïve subjects as they saw simple narratives made up of a first visual image depicting a human event, followed by a second that was either a sequentially coherent narrat…

Optical tomography from focus

2007

A model and a method providing a 3D reconstruction of a given translucent object from a series of image acquisitions performed with various focus tunings is proposed. The object is imaged by transmission; refraction, reflection and diffusion effects are neglected. It is modeled as a stack of translucent parallel slices and the acquisition process can be described by a set of linear equations. We propose an efficient inversion technique with O(n) complexity, allowing practical applications with a simple laptop computer in a very reasonable time. Examples of results obtained with a simulated 3D translucent object are presented and discussed.

Segmentation of Positron Emission Tomography Images Using Multi-atlas Anatomical Magnetic Resonance Imaging (MRI)

2021

Positron emission tomography (PET), is a medical imaging technique, it provides information about the body’s cellular function rather than its anatomy. However, due to the functional nature of PET images, locating the anatomical structures in such an image remains a challenging task, indeed, PET images only provide very little anatomical information. Segmentation of PET images, therefore, requires the intervention of a medical expert. The expert proceeds to a manual segmentation of a volume slice by slice, which turns out to be very tedious and costly in terms of time. In this article, we present, evaluate, and make available a multi-atlas approach for automatically segmenting human brain P…

Hybrid segmentation and virtual bronchoscopy based on CT images1

2004

Rationale and objectives Introduction of combination of the segmentation tool SegoMeTex and the virtual endoscopy system VIVENDI to perform virtual endoscopic inspections of the human lung. This virtual bronchoscopy system enables visualization of the tracheobronchial tree down to seventh generation. Furthermore, the modified virtual system visualizes hidden structures such as segmented vascular system or tumors. Materials and methods The segmentation is based on image data acquired by a multislice computed tomography scanner. SegoMeTex is used to segment the tracheobronchial tree by a hybrid system with minimal user action. Similarly, the complementary pulmonary arterial can be segmented, …

Evaluation of MRI and cannabinoid type 1 receptor PET templates constructed using DARTEL for spatial normalization of rat brains

2015

Purpose: Image registration is one prerequisite for the analysis of brain regions in magnetic-resonance-imaging (MRI) or positron-emission-tomography (PET) studies. Diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) is a nonlinear, diffeomorphic algorithm for image registration and construction of image templates. The goal of this small animal study was (1) the evaluation of a MRI and calculation of several cannabinoid type 1 (CB1) receptor PET templates constructed using DARTEL and (2) the analysis of the image registration accuracy of MR and PET images to their DARTEL templates with reference to analytical and iterative PET reconstruction algorithms. Methods:…

Suppression of phase ambiguity in digital holography by using partial coherence or specimen rotation

2008

In this paper we present two approaches for extracting the surface profile as well as obtaining 3D imaging of near field objects by usage of partial coherence and digital holography. In the first approach a light source with given temporal partial coherence is used to illuminate a near field object. The reflected light is interfered with the reference source. By computing the local contrast of the generated fringes one may estimate the 3D topography and the profile of the object. This approach extracts the 3D information from a single image, and its accuracy does not depend on triangulation angle like in fringe projection methods. The second approach is tomography based. There we illuminate…