Sfoglia per Soggetto "Image segmentation"
Items 1-20 di 36
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Advanced block detection and quantification of fibrotic areas in microscopy images of obstructive nephropathy
(2012)Obstructive nephropathy is not a rare disease and experts need a tool, which will provide them fast and accurate reproducible results for disease assessment. In this work we deal with the analysis of biopsy images for the ... -
Advanced cancer cell characterization and quantification of microscopy images
(2012)In this paper we present an advanced image analysis tool for the accurate characterization and quantification of cancer and apoptotic cells in microscopy images. Adaptive thresholding and Support Vector Machines classifiers ... -
Automated detection of streaks in dermoscopy images
(2015)In this paper we present a novel algorithm for the detection of dark linear structures, which appear in digital dermoscopy images of skin lesions and they are called as streaks in relevant literature. The proposed algorithm ... -
Bimodal CT/MRI-based segmentation method for intervertebral disc boundary extraction
(2020)Intervertebral disc (IVD) localization and segmentation have triggered intensive research efforts in the medical image analysis community, since IVD abnormalities are strong indicators of various spinal cord-related ... -
Cancer cells detection and pathology quantification utilizing image analysis techniques
(2012)This paper presents an advanced image analysis tool for the accurate and fast characterization and quantification of cancer and apoptotic cells in microscopy images utilizing adaptive thresholding and a Support Vector ... -
Classifying mammography images by using fuzzy cognitive maps and a new segmentation algorithm
(2018)Mammography is one of the best techniques for the early detection of breast cancer. In this chapter, a method based on fuzzy cognitive map (FCM) and its evolutionary-based learning capabilities is presented for classifying ... -
Computer Vision and Pattern Recognition for the Analysis of 2D/3D Remote Sensing Data in Geoscience: A Survey
(2022)Historically, geoscience has been a prominent domain for applications of computer vision and pattern recognition. The numerous challenges associated with geoscience-related imaging data, which include poor imaging quality, ... -
A Deep Learning Approach to Object Affordance Segmentation
(2020)Learning to understand and infer object functionalities is an important step towards robust visual intelligence. Significant research efforts have recently focused on segmenting the object parts that enable specific types ... -
Deep sensorimotor learning for RGB-D object recognition
(2020)Research findings in cognitive neuroscience establish that humans, early on, develop their understanding of real-world objects by observing others interact with them or by performing active exploration and physical ... -
Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification
(2018)This paper proposes a novel methodology for automatic detection and localization of gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed with weakly annotated images, using only ... -
Digital image processing: Clinical applications and challenges in cosmetics
(2016)Digital image processing and analysis of medical images can effectively support medical diagnosis with valuable tools including automatic detection, recognition segmentation and measurement of visible entities of interest. ... -
Endoscopic single-image size measurements
(2020)In the practice of clinical gastrointestinal endoscopy, precise estimation of the size of a lesion/finding, such as a polyp, is quintessential in diagnosis, e.g. risk estimation for malignancy. However, various studies ... -
Estimation of robot position and orientation using a stationary fisheye camera
(2015)A core problem in robotics is the determination of the location and pose of a mobile robot in its environment. The localization is a basic operation, which must be successfully carried out in complex environments using ... -
Exploiting morphology and texture of 3D tumor models in DTI for differentiating glioblastoma multiforme from solitary metastasis
(2018)Ambiguous imaging appearance of Glioblastoma Multiforme (GBM) and solitary Metastasis (MET) is a challenge to conventional Magnetic Resonance Imaging (MRI) based diagnosis, leading to exploitation of advanced MRI techniques, ... -
Exploring ROI size in deep learning based lipreading
(2017)Automatic speechreading systems have increasingly exploited deep learning advances, resulting in dramatic gains over traditional methods. State-of-the-art systems typically employ convolutional neural networks (CNNs), ... -
Fisheye camera modeling for human segmentation refinement in indoor videos
(2013)In this paper, we concentrate on refining the results of segmenting human presence from indoors videos acquired by a fisheye camera, using a 3D mathematical model of the camera. The model has been calibrated according to ... -
H-V shadow detection based on electromagnetism-like optimization
(2021)Shadow detection is useful in a variety of image analysis applications, as it can improve scene understanding. Most of the recent shadow detection approaches use near-infrared (NIR) cameras and deep learning to provide ... -
Image Processing and Classification Method Appropriate for Extensible Mobile Applications
(2019)The image processing technique described in this paper can be used for the classification of photographs that display an object of interest. Spots on the object having distinct color surrounded by a potential halo are ... -
Image Segmentation based on Determinative Brain Storm optimization
(2020)Brain Storm optimization (BSO) is a swarm-based, metaheuristic for global optimization, which has been inspired by the collective behavior of human beings. In this work, a novel BSO-based variant, Determinative BSO (DBSO), ... -
Incorporating diffusion-weighted imaging in a diagnostic algorithm for multiparametric MR mammography
(2022)Background: Apparent diffusion coefficient (ADC) measurements are not incorporated in BI-RADS classification. Purpose: To assess the probability of malignancy of breast lesions at magnetic resonance mammography (MRM) at 3 ...