Search results for "VISION"
showing 10 items of 5066 documents
Cell Cycle: The Life Cycle of a Cell
2013
“Where a cell arises, there must be a previous cell”. This early statement of Rudolf Virchow already points to the process that is called cell cycle. It describes a series of events leading to cell division and duplication and can be sectioned into phases that are controlled by a collection of proteins interacting with each other, the cyclines and the cycline-dependent kinases. It is mandatory that DNA replication is conservative meaning that its structure and sequence remain unaltered while the DNA is duplicated before the cell actually divides. Checkpoints are responsible for the supervision, proteins such as p53 and RB being the key protagonists in cell cycle control. Upon DNA damage rec…
Interrelationship Among Morphology, Metabolism, and Proliferation of Tumor Cells in Monolayer and Spheroid Culture
1989
Previous investigations have indicated a positive correlation between the proliferative and metabolic activities of tumor cells in monolayer culture (Freyer et al., 1984; Freyer and Sutherland, 1985; Walenta and Mueller-Klieser, 1987). On the other hand, no difference in the local oxygen consumption has been found between highly proliferating outer cell areas and non-proliferating inner cellular regions in multicellular tumor spheroids (Mueller-Klieser, 1984, 1987). Therefore, the interrelationship among metabolism, proliferation, and cellular morphology was investigated systematically in tumor cells both in monolayer and spheroid culture.
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.
Comparative assessment of brain activity during depth perception of stereoscopic and volumetric images
2020
Recent advancements in visualization systems have triggered a growing demand for the objective and accurate comparison of user cognitive requirements when perceiving three-dimensional images demonstrated in different ways. In this work, we present the first comparative assessment of brain activity in subjects viewing stereoscopic images and volumetric images. Electroencephalography was employed to assess the short-term changes in event related potentials and neural oscillations which were further interpreted in terms of cognitive requirements for relative depth judgments. As a result, considerably higher activity have been registered in the beta band and gamma band in case of judging relati…
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…
Exploring Frequency-dependent Brain Networks from ongoing EEG using Spatial ICA during music listening
2019
AbstractRecently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. Although most efforts focusing on exploring the listening brain have been made through functional magnetic resonance imaging (fMRI), sensor-level electro- or magnetoencephalography (EEG/MEG) technique, little is known about how neural rhythms are involved in the brain network activity under naturalistic stimuli. This study exploited cortical oscillations through analysis of ongoing EEG and musical feature during free-listening to music. We used a data-driven method t…
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, …
GPCALMA: An Italian mammographic database of digitized images for research
2006
In this work the implementation of a database of digitized mammograms is described. The digitized images were collected since 1999 by a community of physicists in collaboration with radiologists in several Italian hospitals, as a first step in order to develop and implement a Computer Aided Detection (CAD) system. 3369 mammograms were collected from 967 patients; they were classified according to the type and the morphology of the lesions, the type of the breast tissue and the type of pathologies. A dedicated Graphical User Interface was developed for mammography visualization and processing, in order to support the medical diagnosis directly on a high-resolution screen. The database has be…
SIFT Texture Description for Understanding Breast Ultrasound Images
2014
Texture is a powerful cue for describing structures that show a high degree of similarity in their image intensity patterns. This paper describes the use of Self-Invariant Feature Transform (SIFT), both as low-level and high-level descriptors, applied to differentiate the tissues present in breast US images. For the low-level texture descriptors case, SIFT descriptors are extracted from a regular grid. The high-level texture descriptor is build as a Bag-of-Features (BoF) of SIFT descriptors. Experimental results are provided showing the validity of the proposed approach for describing the tissues in breast US images.
Image Processors for Digital Angiography Algorithms and Architectures
1986
After a period of experimental and clinical development,(1–9) digital processing of angiographic X-ray video image sequences is now routinely applied in clinical and research work. The clinical advantages offered by this approach have been discussed in several reports.(10–12) The primary application is the improved visualization of regions of the heart and circulation opacified by X-ray contrast material during angiographic and angiocardiographic examinations. More complex techniques are being developed for improved functional analysis based on digitized angiograms. Technically, the digital techniques also potentially offer improved means of acquiring, storing, and handling images when comp…