Search results for "Image Segmentation"
showing 10 items of 234 documents
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…
Semi-automatic detection of skin malformations by analysis of spectral images
2013
The multi-spectral imaging technique to reveal skin malformations has been described in this work. Four spectral images taken at polarized monochromatic LED illumination (450nm, 545nm, 660nm and 940 nm) and polarized white LED light imaged by CMOS sensor via cross-oriented polarizing filter were analyzed to calculate chromophore maps. The algorithm based on skin color analysis and user-defined threshold selection allows highlighting of skin areas with predefined chromophore concentration semi-automatically. Preliminary results of clinical tests are presented.
Neuro-radiosurgery treatments: MRI brain tumor seeded image segmentation based on a cellular automata model
2016
Gross Tumor Volume (GTV) segmentation on medical images is an open issue in neuro-radiosurgery. Magnetic Resonance Imaging (MRI) is the most promi-nent modality in radiation therapy for soft-tissue anatomical districts. Gamma Knife stereotactic neuro-radiosurgery is a mini-invasive technique used to deal with inaccessible or insufficiently treated tumors. During the planning phase, the GTV is usually contoured by radiation oncologists using a manual segmentation procedure on MR images. This methodology is certainly time-consuming and op-erator-dependent. Delineation result repeatability, in terms of both intra- and inter-operator reliability, is only obtained by using computer-assisted appr…
A CAD system for nodule detection in low-dose lung CTs based on region growing and a new active contour model
2007
A computer-aided detection (CAD) system for the selection of lung nodules in computer tomography (CT) images is presented. The system is based on region growing (RG) algorithms and a new active contour model (ACM), implementing a local convex hull, able to draw the correct contour of the lung parenchyma and to include the pleural nodules. The CAD consists of three steps: (1) the lung parenchymal volume is segmented by means of a RG algorithm; the pleural nodules are included through the new ACM technique; (2) a RG algorithm is iteratively applied to the previously segmented volume in order to detect the candidate nodules; (3) a double-threshold cut and a neural network are applied to reduce…
Hybrid segmentation and exploration of the human lungs
2004
Segmentation of the tracheo-bronchial tree of the lungs is notoriously difficult. This is due to the fact that the small size of some of the anatomical structures is subject to partial volume effects. Furthermore, the limited intensity contrast between the participating materials (air, blood, and tissue) increases the segmentation of difficulties. In this paper, we propose a hybrid segmentation method which is based on a pipeline of three segmentation stages to extract the lower airways down to the seventh generation of the bronchi. User interaction is limited to the specification of a seed point inside the easily detectable trachea at the upper end of the lower airways. Similarly, the comp…
Graph-matching based CTA.
2009
Separating bone, calcification, and vessels in computer tomography angiography (CTA) allows for a detailed diagnosis of vessel stenosis. This paper presents a new, graph-based technique that solves this difficult problem with high accuracy. The approach requires one native data set and one that is contrast enhanced. On each data set, an attributed level-graph is derived and both graphs are matched by dynamic programming to differentiate between bone, on one hand side, and vessel/calcification on the other hand side. Lumen and calcified regions are then separated by a profile technique. Evaluation is based on data from vessels of pelvis and lower extremities of elderly patients. Due to subst…
NeuronAlg: An Innovative Neuronal Computational Model for Immunofluorescence Image Segmentation
2023
Background: Image analysis applications in digital pathology include various methods for segmenting regions of interest. Their identification is one of the most complex steps and therefore of great interest for the study of robust methods that do not necessarily rely on a machine learning (ML) approach. Method: A fully automatic and optimized segmentation process for different datasets is a prerequisite for classifying and diagnosing indirect immunofluorescence (IIF) raw data. This study describes a deterministic computational neuroscience approach for identifying cells and nuclei. It is very different from the conventional neural network approaches but has an equivalent quantitative and qu…
Hypervisor-Based White Listing of Executables
2019
We describe an efficient system for ensuring code integrity of an operating system (OS), both its own code and application code. The proposed system can protect from an attacker who has full control over the OS kernel. An evaluation of the system's performance suggests the induced overhead is negligible. peerReviewed
Emotions and Activity Recognition System Using Wearable Device Sensors
2021
Nowadays machines have become extremely smart, there are a lot of existing services that seemed to be unexpectable and futuristic decades or even a few years ago. However, artificial intelligence is still far from human intelligence, machines do not have feelings, consciousness, and intuition. How can we help machines to learn about human feelings and understand their needs better? People take their devices wherever they go, what can devices tell us about their owners? Personal preferences and needs are dependent on emotional and situational contexts. Therefore, emotional and activity aware gadgets would be more intuitive and provide more appropriate information to users. Contemporary weara…
An Integrated Method for Image Retrieval
1995
This paper presents an information fusion method for image retrieval; the retrieval strategy is based on statistical and geometrical features extracted from sub-images. Our goal is to find a set of best similar images related to a prototype image; this goal may be obtained according to image content rather than symbolic attributes. MRI (Magnetic Resonance Imaging) images and astronomical images have been adopted to test the method. Main steps of the procedure to retrieve images are: (l) Segmentation, (2) Matching, and (3) Decision. The first step involves four clusters co-operating segmentation algorithms; in the matching step, a sets of candidate similar images is provided; finally an info…