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Texture classification

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https://www.readbyqxmd.com/read/28715442/combining-random-forest-with-multi-block-local-binary-pattern-feature-selection-for-multiclass-head-pose-estimation
#1
Min-Joo Kang, Jung-Kyung Lee, Je-Won Kang
A new head pose estimation technique based on Random Forest (RF) and texture features for facial image analysis using a monocular camera is proposed in this paper, especially about how to efficiently combine the random forest and the features. In the proposed technique a randomized tree with useful attributes is trained to improve estimation accuracy and tolerance of occlusions and illumination. Specifically, a number of features including Multi-scale Block Local Block Pattern (MB-LBP) are extracted from an image, and random features such as the MB-LBP scale parameters, a block coordinate, and a layer of an image pyramid in the feature pool are used for training the tree...
2017: PloS One
https://www.readbyqxmd.com/read/28712700/radiomic-analysis-of-dce-mri-for-prediction-of-response-to-neoadjuvant-chemotherapy-in-breast-cancer-patients
#2
Ming Fan, Guolin Wu, Hu Cheng, Juan Zhang, Guoliang Shao, Lihua Li
OBJECTIVES: To enhance the accurate prediction of the response to neoadjuvant chemotherapy (NAC) in breast cancer patients by using a quantitative analysis of dynamic enhancement magnetic resonance imaging (DCE-MRI). MATERIALS AND METHODS: A dataset of 57 cancer patients with breast DCE-MR images acquired before NAC was used. Among them, 47 patients were Responders, and 10 patients were non-Responders based on the RECIST criteria. The breast regions were segmented on the MR images, and a total of 158 radiomic features were computed to represent the morphologic, dynamic, and the texture of the tumors as well as the background parenchymal features...
June 28, 2017: European Journal of Radiology
https://www.readbyqxmd.com/read/28707546/a-computer-aided-diagnosis-cad-scheme-for-pretreatment-prediction-of-pathological-response-to-neoadjuvant-therapy-using-dynamic-contrast-enhanced-mri-texture-features
#3
Valentina Giannini, Simone Mazzetti, Agnese Marmo, Filippo Montemurro, Daniele Regge, Laura Martincich
OBJECTIVES: To assess whether a computer aided diagnosis (CAD) system can predict pathological response (pCR) to neoadjuvant chemotherapy (NAC) prior to treatment using texture features. MATERIALS AND METHODS: Response to treatment of 44 patients was defined according to the histopatology of resected tumour and extracted axillary nodes in two ways: a) pCR+ (Smith's grade=5) vs pCR- (Smith's grade<5); b) pCRN+ (pCR+ and absence of residual lymph node metastases) vs pCRN-...
July 14, 2017: British Journal of Radiology
https://www.readbyqxmd.com/read/28705145/texture-based-classification-of-different-single-liver-lesion-based-on-spair-t2w-mri-images
#4
Zhenjiang Li, Yu Mao, Wei Huang, Hongsheng Li, Jian Zhu, Wanhu Li, Baosheng Li
BACKGROUND: To assess the feasibility of texture analysis (TA) based on spectral attenuated inversion-recovery T2 weighted magnetic resonance imaging (SPAIR T2W-MRI) for the classification of hepatic hemangioma (HH), hepatic metastases (HM) and hepatocellular carcinoma (HCC). METHODS: The SPAIR T2W-MRI data of 162 patients with HH (n=55), HM (n=67) and HCC (n=40) were retrospectively analyzed. We used two independent cohorts for training (n = 112 patients) and validation (n = 50 patients)...
July 13, 2017: BMC Medical Imaging
https://www.readbyqxmd.com/read/28703115/incidental-diagnosis-of-the-tall-cell-variant-of-the-papillary-microcarcinoma-of-the-thyroid-gland-requires-completion-lymphadenectomy-case-report
#5
I Bartella, F Meyer, K Frauenschläger, K Reschke, Th Wallbaum, B Buth, C Bruns, C Chiapponi
Papillary thyroid carcinoma is the most common neoplasm of the thyroid gland which is usually associated with a very good prognosis. The aim of this case report is to present the disease course of a rare tumor of the thyroid gland, which is worthwhile due to its extraordinary appearance and specific management. A 46-year-old patient presented with a pronounced right-sided, but bilateral, multinodular goiter, with a volume of approximately 80 mL, as assessed on ultrasonography. Surgical removal was indicated as scintigraphy showed a 4-cm cold nodule that almost completely took up the right thyroid lobe...
June 30, 2017: Polski Przeglad Chirurgiczny
https://www.readbyqxmd.com/read/28700903/computer-based-classification-of-chromoendoscopy-images-using-homogeneous-texture-descriptors
#6
Hussam Ali, Muhammad Sharif, Mussarat Yasmin, Mubashir Husain Rehmani
Computer-aided analysis of clinical pathologies is a challenging task in the field of medical imaging. Specifically, the detection of abnormal regions in the frames collected during an endoscopic session is difficult. The variations in the conditions of image acquisition, such as field of view or illumination modification, make it more demanding. Therefore, the design of a computer-assisted diagnostic system for the recognition of gastric abnormalities requires features that are robust to scale, rotation, and illumination variations of the images...
July 5, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28697731/texture-analysis-of-pulmonary-parenchymateous-changes-related-to-pulmonary-thromboembolism-in-dogs-a-novel-approach-using-quantitative-methods
#7
C B Marschner, M Kokla, J M Amigo, E A Rozanski, B Wiinberg, F J McEvoy
BACKGROUND: Diagnosis of pulmonary thromboembolism (PTE) in dogs relies on computed tomography pulmonary angiography (CTPA), but detailed interpretation of CTPA images is demanding for the radiologist and only large vessels may be evaluated. New approaches for better detection of smaller thrombi include dual energy computed tomography (DECT) as well as computer assisted diagnosis (CAD) techniques. The purpose of this study was to investigate the performance of quantitative texture analysis for detecting dogs with PTE using grey-level co-occurrence matrices (GLCM) and multivariate statistical classification analyses...
July 11, 2017: BMC Veterinary Research
https://www.readbyqxmd.com/read/28697402/functional-biocompatibility-testing-of-silicone-breast-implants-and-a-novel-classification-system-based-on-surface-roughness
#8
S Barr, E W Hill, A Bayat
PURPOSE: Increasing numbers of women undergo breast implantation for cosmetic and reconstructive purposes. Contracture of the fibrous capsule, which encases the implant leads to significant pain and reoperation. Texture, wettability and the cellular reaction to implant surfaces are poorly understood determinants of implant biocompatibility. The aim of this study was to evaluate the in-vitro characteristics of a range of commercial available implants using a macrophage based assay of implant biocompatibility and a quantitative assessment of wettability and texture...
June 27, 2017: Journal of the Mechanical Behavior of Biomedical Materials
https://www.readbyqxmd.com/read/28692962/bilinear-convolutional-neural-networks-for-fine-grained-visual-recognition
#9
Tsung-Yu Lin, Aruni RoyChowdhury, Subhransu Maji
We present a simple and effective architecture for fine-grained recognition called Bilinear Convolutional Neural Networks (B-CNNs). These networks represent an image as a pooled outer product of features derived from two CNNs and capture localized feature interactions in a translationally invariant manner. B-CNNs are related to orderless texture representations built on deep features but can be trained in an end-to-end manner. Our most accurate model obtains 84.1%, 79.4%, 84.5% and 91.3% per-image accuracy on the Caltech-UCSD birds [66], NABirds [63], FGVC aircraft [42], and Stanford cars [33] dataset respectively and runs at 30 frames-per-second on a NVIDIA Titan X GPU...
July 4, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28685320/can-laws-be-a-potential-pet-image-texture-analysis-approach-for-evaluation-of-tumor-heterogeneity-and-histopathological-characteristics-in-nsclc
#10
Seyhan Karacavus, Bülent Yılmaz, Arzu Tasdemir, Ömer Kayaaltı, Eser Kaya, Semra İçer, Oguzhan Ayyıldız
We investigated the association between the textural features obtained from (18)F-FDG images, metabolic parameters (SUVmax, SUVmean, MTV, TLG), and tumor histopathological characteristics (stage and Ki-67 proliferation index) in non-small cell lung cancer (NSCLC). The FDG-PET images of 67 patients with NSCLC were evaluated. MATLAB technical computing language was employed in the extraction of 137 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run length matrix (GLRLM), and Laws' texture filters...
July 6, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28667318/automatic-detection-of-galaxy-type-from-datasets-of-galaxies-image-based-on-image-retrieval-approach
#11
Mohamed Abd El Aziz, I M Selim, Shengwu Xiong
This paper presents a new approach for the automatic detection of galaxy morphology from datasets based on an image-retrieval approach. Currently, there are several classification methods proposed to detect galaxy types within an image. However, in some situations, the aim is not only to determine the type of galaxy within the queried image, but also to determine the most similar images for query image. Therefore, this paper proposes an image-retrieval method to detect the type of galaxies within an image and return with the most similar image...
June 30, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28665361/a-study-of-deep-cnn-based-classification-of-open-and-closed-eyes-using-a-visible-light-camera-sensor
#12
Ki Wan Kim, Hyung Gil Hong, Gi Pyo Nam, Kang Ryoung Park
The necessity for the classification of open and closed eyes is increasing in various fields, including analysis of eye fatigue in 3D TVs, analysis of the psychological states of test subjects, and eye status tracking-based driver drowsiness detection. Previous studies have used various methods to distinguish between open and closed eyes, such as classifiers based on the features obtained from image binarization, edge operators, or texture analysis. However, when it comes to eye images with different lighting conditions and resolutions, it can be difficult to find an optimal threshold for image binarization or optimal filters for edge and texture extraction...
June 30, 2017: Sensors
https://www.readbyqxmd.com/read/28663266/relationship-between-glioblastoma-heterogeneity-and-survival-time-an-mr-imaging-texture-analysis
#13
Y Liu, X Xu, L Yin, X Zhang, L Li, H Lu
BACKGROUND AND PURPOSE: The heterogeneity of glioblastoma contributes to the poor and variant prognosis. The aim of this retrospective study was to assess the glioblastoma heterogeneity with MR imaging textures and to evaluate its impact on survival time. MATERIALS AND METHODS: A total of 133 patients with primary glioblastoma who underwent postcontrast T1-weighted imaging (acquired before treatment) and whose data were filed with the survival times were selected from the Cancer Genome Atlas...
June 29, 2017: AJNR. American Journal of Neuroradiology
https://www.readbyqxmd.com/read/28654965/mid-level-perceptual-features-contain-early-cues-to-animacy
#14
Bria Long, Viola S Störmer, George A Alvarez
While substantial work has focused on how the visual system achieves basic-level recognition, less work has asked about how it supports large-scale distinctions between objects, such as animacy and real-world size. Previous work has shown that these dimensions are reflected in our neural object representations (Konkle & Caramazza, 2013), and that objects of different real-world sizes have different mid-level perceptual features (Long, Konkle, Cohen, & Alvarez, 2016). Here, we test the hypothesis that animates and manmade objects also differ in mid-level perceptual features...
June 1, 2017: Journal of Vision
https://www.readbyqxmd.com/read/28654820/the-potential-value-of-preoperative-mri-texture-and-shape-analysis-in-grading-meningiomas-a-preliminary-investigation
#15
Peng-Fei Yan, Ling Yan, Ting-Ting Hu, Dong-Dong Xiao, Zhen Zhang, Hong-Yang Zhao, Jun Feng
OBJECT: Preoperative knowledge of meningioma grade is essential for planning treatment and surgery. The purpose of this study was to investigate the diagnostic value of MRI texture and shape analysis in grading meningiomas. METHODS: A surgical database was reviewed to identify meningioma patients who had undergone tumor resection between January 2015 and December 2016. Preoperative MR images were retrieved and analyzed. Texture and shape analysis was conducted to quantitatively evaluate tumor heterogeneity and morphology...
June 24, 2017: Translational Oncology
https://www.readbyqxmd.com/read/28654222/imprint-cytology-based-breast-malignancy-screening-an-efficient-nuclei-segmentation-technique
#16
M Saha, I Arun, S Agarwal, R Ahmed, S Chatterjee, C Chakraborty
Imprint cytology (IC) refers to one of the most reliable, rapid and affordable techniques for breast malignancy screening; where shape variation of H&E stained nucleus is examined by the pathologists. This work aims at developing an automated and efficient segmentation algorithm by integrating Lagrange's interpolation and superpixels in order to delineate overlapped nuclei of breast cells (normal and malignant). Subsequently, a computer assisted IC tool has been designed for breast cancer (BC) screening. The proposed methodology consists of mainly three subsections: gamma correction for preprocessing, single nuclei segmentation and segmentation of overlapping nuclei...
June 27, 2017: Journal of Microscopy
https://www.readbyqxmd.com/read/28653477/radiomic-analysis-of-soft-tissues-sarcomas-can-distinguish-intermediate-from-high-grade-lesions
#17
Valentina D A Corino, Eros Montin, Antonella Messina, Paolo G Casali, Alessandro Gronchi, Alfonso Marchianò, Luca T Mainardi
PURPOSE: To assess the feasibility of grading soft tissue sarcomas (STSs) using MRI features (radiomics). MATERIALS AND METHODS: MRI (echo planar SE, 1.5T) from 19 patients with STSs and a known histological grading, were retrospectively analyzed. The apparent diffusion coefficient (ADC) maps, obtained by diffusion-weighted imaging acquisitions, were analyzed through 65 radiomic features, intensity-based (first order statistics, FOS) and texture (gray level co-occurrence matrix, GLCM; and gray level run length matrix, GLRLM) features...
June 27, 2017: Journal of Magnetic Resonance Imaging: JMRI
https://www.readbyqxmd.com/read/28653016/gland-segmentation-in-prostate-histopathological-images
#18
Malay Singh, Emarene Mationg Kalaw, Danilo Medina Giron, Kian-Tai Chong, Chew Lim Tan, Hwee Kuan Lee
Glandular structural features are important for the tumor pathologist in the assessment of cancer malignancy of prostate tissue slides. The varying shapes and sizes of glands combined with the tedious manual observation task can result in inaccurate assessment. There are also discrepancies and low-level agreement among pathologists, especially in cases of Gleason pattern 3 and pattern 4 prostate adenocarcinoma. An automated gland segmentation system can highlight various glandular shapes and structures for further analysis by the pathologist...
April 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28653015/classification-of-breast-masses-in-ultrasound-images-using-self-adaptive-differential-evolution-extreme-learning-machine-and-rough-set-feature-selection
#19
Kadayanallur Mahadevan Prabusankarlal, Palanisamy Thirumoorthy, Radhakrishnan Manavalan
A method using rough set feature selection and extreme learning machine (ELM) whose learning strategy and hidden node parameters are optimized by self-adaptive differential evolution (SaDE) algorithm for classification of breast masses is investigated. A pathologically proven database of 140 breast ultrasound images, including 80 benign and 60 malignant, is used for this study. A fast nonlocal means algorithm is applied for speckle noise removal, and multiresolution analysis of undecimated discrete wavelet transform is used for accurate segmentation of breast lesions...
April 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28646177/hyperspectral-imaging-for-presymptomatic-detection-of-tobacco-disease-with-successive-projections-algorithm-and-machine-learning-classifiers
#20
Hongyan Zhu, Bingquan Chu, Chu Zhang, Fei Liu, Linjun Jiang, Yong He
We investigated the feasibility and potentiality of presymptomatic detection of tobacco disease using hyperspectral imaging, combined with the variable selection method and machine-learning classifiers. Images from healthy and TMV-infected leaves with 2, 4, and 6 days post infection were acquired by a pushbroom hyperspectral reflectance imaging system covering the spectral range of 380-1023 nm. Successive projections algorithm was evaluated for effective wavelengths (EWs) selection. Four texture features, including contrast, correlation, entropy, and homogeneity were extracted according to grey-level co-occurrence matrix (GLCM)...
June 23, 2017: Scientific Reports
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