نتایج جستجو برای: image segmentation

تعداد نتایج: 413875  

Journal: :international journal of hospital research 2013
toktam khatibi mohammad mehdi sepehri pejman shadpour

background and objectives: identification of surgical instruments in laparoscopic video images has several biomedical applications. while several methods have been proposed for accurate detection of surgical instruments, the accuracy of these methods is still challenged high complexity of the laparoscopic video images. this paper introduces a surgical instrument detection framework (sidf) for a...

Journal: :journal of computer and robotics 0
ali borumandnia islamic azad university of south tehran jamshid shanbehzadeh tarbiat moalem

this paper presents, a hybrid method, low-resolution and high-resolution, for persian page segmentation. in the low-resolution page segmentation, a pyramidal image structure is constructed for multiscale analysis and segments document image to a set of regions. by high-resolution page segmentation, by connected components analysis, each region is segmented to homogeneous regions and identifying...

We first describe how to “fuzzify” the estimated binary columns to create a [0,1]-valued column. Werefer to this [0,1] -valued column as the soft segmentation column of the noisy spectrogram column.Similarly to the collection of soft segmentation columns as the soft segmentation image, or simply asthe soft segmentation. The band-dependent posterior probability that the hard segmentation columnv...

Background: Brain tissue segmentation for delineation of 3D anatomical structures from magnetic resonance (MR) images can be used for neuro-degenerative disorders, characterizing morphological differences between subjects based on volumetric analysis of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), but only if the obtained segmentation results are correct. Due to image arti...

Journal: :journal of medical signals and sensors 0
raheleh kafieh hossein rabbani saeed kermani

optical coherence tomography (oct) is a powerful imaging modality used to image various aspects of biological tissues, such as structural information, blood flow, elastic parameters, change of polarization states, and molecular content [1]. in contrast to oct technology development which has been a field of active research since 1991, oct image segmentation has only been more fully explored dur...

Background and Objectives: Identification of surgical instruments in laparoscopic video images has several biomedical applications. While several methods have been proposed for accurate detection of surgical instruments, the accuracy of these methods is still challenged high complexity of the laparoscopic video images. This paper introduces a Surgical Instrument Detection Framework (SIDF) for a...

Image segmentation is an essential and critical process in image processing and pattern recognition. In this paper we proposed a textured-based method to segment an input image into regions. In our method an entropy-based textured map of image is extracted, followed by an histogram equalization step to discriminate different regions. Then with the aim of eliminating unnecessary details and achi...

Mohammad Reza Meybodi Peyman Rasouli

Image segmentation is an important task in image processing and computer vision which attract many researchers attention. There are a couple of information sets pixels in an image: statistical and structural information which refer to the feature value of pixel data and local correlation of pixel data, respectively. Markov random field (MRF) is a tool for modeling statistical and structural inf...

Journal: :journal of medical signals and sensors 0
vahid mohammadi saffarzadeh alireza osareh bita shadgar

detecting blood vessels is an important task in retinal image analysis.  the task is more challenging with the presence of bright and dark lesions in retinal images. here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. first, the negative impact of bright lesions is reduced by using k-means segmentation in a perceptive sp...

Journal: :journal of medical signals and sensors 0
hassan khotanlou mahlagha afrasiabi

this paper introduces a novel methodology for the segmentation of brain ms lesions in mri volumes using a new clustering algorithm named scpfcm.  scpfcm uses membership, typicality and spatial information to cluster each voxel. the proposed method relies on an initial segmentation of ms lesions in t1-w and t2-w images by applying scpfcm algorithm, and the t1 image is then used as a mask and is ...

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