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Histogram analysis texture analysis

Sigmund Ytre-Hauge, Julie A Dybvik, Arvid Lundervold, Øyvind O Salvesen, Camilla Krakstad, Kristine E Fasmer, Henrica M Werner, Balaji Ganeshan, Erling Høivik, Line Bjørge, Jone Trovik, Ingfrid S Haldorsen
BACKGROUND: Improved methods for preoperative risk stratification in endometrial cancer are highly requested by gynecologists. Texture analysis is a method for quantification of heterogeneity in images, increasingly reported as a promising diagnostic tool in various cancer types, but largely unexplored in endometrial cancer. PURPOSE: To explore whether tumor texture parameters from preoperative MRI are related to known prognostic features (deep myometrial invasion, cervical stroma invasion, lymph node metastases, and high-risk histological subtype) and to outcome in endometrial cancer patients...
August 13, 2018: Journal of Magnetic Resonance Imaging: JMRI
Angeliki Theodosi, Dimitris Glotsos, Spiros Kostopoulos, Ioannis Kalatzis, Vassiliki Tzelepi, Panagiota Ravazoula, Pantelis Asvestas, Dionisis Cavouras, George Sakellaropoulos
OBJECTIVE: The objective of this study was to study the textural and color changes occurring in the epithelial gland tissue with advancing colorectal cancer (CRC), utilizing immunohistochemical stain for AIB1 expression biopsy material. MATERIAL AND METHODS: Clinical material comprised biopsy specimens of 67 patients with a diagnosis of CRC. Two experienced pathologists used H&E-stained material for grading CRC lesions and immunohistochemical (IHC) stain for AIB1 expression...
August 8, 2018: Applied Immunohistochemistry & Molecular Morphology: AIMM
Haojie Li, Anqin Li, Hui Zhu, Yao Hu, Jiali Li, Liming Xia, Daoyu Hu, Ihab R Kamel, Zhen Li
AIM: To evaluate the diagnostic value of whole-tumor quantitative apparent diffusion coefficient (ADC) histogram and texture analysis for differentiation of minimal fat angiomyolipoma (MFAML) from clear cell renal cell carcinoma (ccRCC). MATERIALS AND METHODS: We retrospectively reviewed 27 patients with MFAML and 113 patients with ccRCC pathologically proven. All patients performed magnetic resonance imaging (MRI) including diffusion-weighted imaging (b = 0, 800s/mm2 )...
August 4, 2018: Academic Radiology
Chengquan Zhou, Dong Liang, Xiaodong Yang, Hao Yang, Jibo Yue, Guijun Yang
The number of wheat ears in the field is very important data for predicting crop growth and estimating crop yield and as such is receiving ever-increasing research attention. To obtain such data, we propose a novel algorithm that uses computer vision to accurately recognize wheat ears in a digital image. First, red-green-blue images acquired by a manned ground vehicle are selected based on light intensity to ensure that this method is robust with respect to light intensity. Next, the selected images are cut to ensure that the target can be identified in the remaining parts...
2018: Frontiers in Plant Science
A Palmisano, A Esposito, P M V Rancoita, A Di Chiara, P Passoni, N Slim, M Campolongo, L Albarello, C Fiorino, R Rosati, A Del Maschio, F De Cobelli
AIM: To evaluate whether perfusion heterogeneity of rectal cancer prior to chemoradiotherapy (CRT) using histogram analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) quantitative parameters can predict response to treatment. MATERIALS AND METHODS: Twenty-one patients with histologically proven rectal adenocarcinoma were enrolled prospectively. All patients underwent 1.5 T DCE-MRI before CRT. Tumour volumes were drawn on Ktrans and Ve maps, using T2-weighted (W) images as reference, and the following first-order texture parameters of Ve and Ktrans values were extracted: 25th, 50th, 75th percentile, mean, standard deviation, skewness, and kurtosis...
July 17, 2018: Clinical Radiology
Carlos López-Gómez, Rafael Ortiz-Ramón, Enrique Mollá-Olmos, David Moratal
The current criteria for diagnosing Alzheimer's disease (AD) require the presence of relevant cognitive deficits, so the underlying neuropathological damage is important by the time the diagnosis is made. Therefore, the evaluation of new biomarkers to detect AD in its early stages has become one of the main research focuses. The purpose of the present study was to evaluate a set of texture parameters as potential biomarkers of the disease. To this end, the ALTEA (ALzheimer TExture Analyzer) software tool was created to perform 2D and 3D texture analysis on magnetic resonance images...
July 19, 2018: Diagnostics
Ting-Wei Fan, Harshawn Malhi, Bino Varghese, Steve Cen, Darryl Hwang, Manju Aron, Nieroshan Rajarubendra, Mihir Desai, Vinay Duddalwar
PURPOSE: The purpose of the study is to determine the feasibility of using computed tomography-based texture analysis (CTTA) in differentiating between urothelial carcinomas (UC) of the bladder from micropapillary carcinomas (MPC) of the bladder. METHODS: Regions of interests (ROIs) of computerized tomography (CT) images of 33 MPCs and 33 UCs were manually segmented and saved. Custom MATLAB code was used to extract voxel information corresponding to the ROI. The segmented tumors were input to a pre-existing radiomics platform with a CTTA panel...
July 18, 2018: Abdominal Radiology
Yun-Xiang Bai, Shu-Hui Zhang, Zhi Fan, Xing-Yu Liu, Xin Zhao, Xi-Zeng Feng, Ming-Zhu Sun
As an excellent model organism, zebrafish have been widely applied in many fields. The accurate identification and tracking of individuals are crucial for zebrafish shoaling behaviour analysis. However, multi-zebrafish tracking still faces many challenges. It is difficult to keep identified for a long time due to fish overlapping caused by the crossings. Here we proposed an improved Histogram of Oriented Gradient (HOG) algorithm to calculate the stable back texture feature map of zebrafish, then tracked multi-zebrafish in a fully automated fashion with low sample size, high tracking accuracy and wide applicability...
July 18, 2018: Scientific Reports
Jiawei Chen, Haibin Chen, Zichun Zhong, Zhuoyu Wang, Brian Hrycushko, Linghong Zhou, Steve Jiang, Kevin Albuquerque, Xuejun Gu, Xin Zhen
BACKGROUND: Better knowledge of the dose-toxicity relationship is essential for safe dose escalation to improve local control in cervical cancer radiotherapy. The conventional dose-toxicity model is based on the dose volume histogram, which is the parameter lacking spatial dose information. To overcome this limit, we explore a comprehensive rectal dose-toxicity model based on both dose volume histogram and dose map features for accurate radiation toxicity prediction. METHODS: Forty-two cervical cancer patients treated with combined external beam radiotherapy (EBRT) and brachytherapy (BT) were retrospectively studied, including 12 with Grade ≥ 2 rectum toxicity and 30 patients with Grade 0-1 toxicity (non-toxicity patients)...
July 6, 2018: Radiation Oncology
Huan Zhang, Wenhua Li, Feixiang Hu, Yiqun Sun, Tingdan Hu, Tong Tong
PURPOSE: The purpose of the study was to determine whether the pre-treated MR texture features of colorectal liver metastases (CRLMs) are predictive of therapeutic response after chemotherapy. METHODS: The study included twenty-six consecutive patients (a total of 193 liver metastasis) with unrespectable CRLMs at our institution from August 2014 to February 2016. Lesions were categorized into either responding group or non-responding group according to changes in size...
July 2, 2018: Abdominal Radiology
Christophe Nioche, Fanny Orlhac, Sarah Boughdad, Sylvain Reuzé, Jessica Goya-Outi, Charlotte Robert, Claire Pellot-Barakat, Michael Soussan, Frédérique Frouin, Irène Buvat
Textural and shape analysis is gaining considerable interest in medical imaging, particularly to identify parameters characterizing tumor heterogeneity and to feed radiomic models. Here we present a free, multiplatform, and easy-to-use freeware called LIFEx, which enables the calculation of conventional, histogram-based textural and shape features from PET, SPECT, MR, CT, and US images, or from any combination of imaging modalities. The application does not require any programming skills and was developed for medical imaging professionals...
June 29, 2018: Cancer Research
Shang-Wen Chen, Wei-Chih Shen, William Tzu-Liang Chen, Te-Chun Hsieh, Kuo-Yang Yen, Jan-Gowth Chang, Chia-Hung Kao
PURPOSE: To understand the association between genetic mutations and radiomics of 2-deoxy-2-[18 F]fluoro-D-glucose ([18 F]FDG) positron emission tomography (PET)/x-ray computed tomography (CT) in patients with colorectal cancer (CRC). PROCEDURES: This study included 74 CRC patients who had undergone preoperative [18 F]FDG PET/CT. A total of 65 PET/CT-related features including intensity, volume-based, histogram, and textural features were calculated. High-resolution melting methods were used for genetic mutation analysis...
June 12, 2018: Molecular Imaging and Biology: MIB: the Official Publication of the Academy of Molecular Imaging
H Akai, K Yasaka, A Kunimatsu, M Nojima, T Kokudo, N Kokudo, K Hasegawa, O Abe, K Ohtomo, S Kiryu
RATIONALE AND OBJECTIVES: To investigate the impact of random survival forest (RSF) classifier trained by radiomics features over the prediction of the overall survival of patients with resectable hepatocellular carcinoma (HCC). MATERIALS AND METHODS: The dynamic computed tomography data of 127 patients (97 men, 30 women; mean age, 68 years) newly diagnosed with resectable HCC were retrospectively analyzed. After manually setting the region of interest to include the tumor within the slice at its maximum diameter, texture analyses were performed with or without a Laplacian of Gaussian filter...
June 14, 2018: Diagnostic and Interventional Imaging
Hui Wu, Xiaojian Chen, Xin Yang, Yalan Tao, Yunfei Xia, Xiaowu Deng, Cheng Zheng, Jared Robbins, Christopher Schultz, X Allen Li
PURPOSE: To investigate radiation-induced changes of computed tomography (CT) textures in parotid glands (PG) to predict acute xerostomia during radiotherapy (RT) for head and neck cancer (HNC). METHODS AND MATERIALS: Daily or fraction kilovoltage CTs acquired using diagnostic CT scanners (eg, in-room CTs) during intensity-modulated RT for 59 HNC patients at 3 institutions were analyzed. The PG contours were generated on selected daily/fraction CTs. A series of histogram-based texture features, including the mean CT number (MCTN) in Hounsfield units, volume, standard deviation, skewness, kurtosis, and entropy for PGs were calculated for each fraction...
May 1, 2018: International Journal of Radiation Oncology, Biology, Physics
Neslihan Kurtul, Nursel Yurttutan, Murat Baykara
OBJECTIVE: The aim of this study was to apply texture analysis to investigate whether there was a change in the lens following radiotherapy. PATIENTS AND METHOD: Patients who received radiotherapy (RT) for head and neck cancer or brain tumour were enrolled. Computed tomography (CT) images taken one month before RT and the most recent images after RT were compared. Entropy values were calculated using lens attenuation values. The lens doses were obtained from the dose-volume histogram data...
June 5, 2018: Journal of X-ray Science and Technology
Anton S Becker, Marcel A Schneider, Moritz C Wurnig, Matthias Wagner, Pierre A Clavien, Andreas Boss
Background: The purpose of this study was to investigate whether any texture features show a correlation with intrahepatic tumor growth before the metastasis is visible to the human eye. Methods: Eight male C57BL6 mice (age 8-10 weeks) were injected intraportally with syngeneic MC-38 colon cancer cells and two mice were injected with phosphate-buffered saline (sham controls). Small animal magnetic resonance imaging (MRI) at 4.7 T was performed at baseline and days 4, 8, 12, 16, and 20 after injection applying a T2-weighted spin-echo sequence...
2018: European radiology experimental
Karoline Skogen, Anselm Schulz, Eirik Helseth, Balaji Ganeshan, Johann Baptist Dormagen, Andrès Server
Background Texture analysis has been done on several radiological modalities to stage, differentiate, and predict prognosis in many oncologic tumors. Purpose To determine the diagnostic accuracy of discriminating glioblastoma (GBM) from single brain metastasis (MET) by assessing the heterogeneity of both the solid tumor and the peritumoral edema with magnetic resonance imaging (MRI) texture analysis (MRTA). Material and Methods Preoperative MRI examinations done on a 3-T scanner of 43 patients were included: 22 GBM and 21 MET...
January 1, 2018: Acta Radiologica
Andrew T Scrima, Meghan G Lubner, E Jason Abel, Thomas C Havighurst, Daniel D Shapiro, Wei Huang, Perry J Pickhardt
PURPOSE: To assess CT texture features of small renal cell carcinomas (≤ 4cm) for association with key pathologic features including protein biomarkers. METHODS: Quantitative CT texture analysis (CTTA) of small renal cancers (≤ 4cm) was performed on non-contrast and portal venous phase abdominal MDCT scans with an ROI drawn at the largest cross-sectional diameter of the tumor using commercially available software. Texture parameters including mean pixel attenuation, the standard deviation (SD) of the pixel distribution histogram, entropy, the mean of positive pixels, the skewness (i...
May 26, 2018: Abdominal Radiology
Sara Moccia, Leonardo S Mattos, Ilaria Patrini, Michela Ruperti, Nicolas Poté, Federica Dondero, François Cauchy, Ailton Sepulveda, Olivier Soubrane, Elena De Momi, Alberto Diaspro, Manuela Cesaretti
PURPOSE: Fast and accurate graft hepatic steatosis (HS) assessment is of primary importance for lowering liver dysfunction risks after transplantation. Histopathological analysis of biopsied liver is the gold standard for assessing HS, despite being invasive and time consuming. Due to the short time availability between liver procurement and transplantation, surgeons perform HS assessment through clinical evaluation (medical history, blood tests) and liver texture visual analysis. Despite visual analysis being recognized as challenging in the clinical literature, few efforts have been invested to develop computer-assisted solutions for HS assessment...
May 23, 2018: International Journal of Computer Assisted Radiology and Surgery
Xinxin Liu, Jian Yang, Shuang Song, Hong Song, Danni Ai, Jianjun Zhu, Yurong Jiang, Yongtian Wang
Liver metabolic information is considered as a crucial diagnostic marker for the diagnosis of fever of unknown origin, and liver recognition is the basis of automatic diagnosis of metabolic information extraction. However, the poor quality of PET and CT images is a challenge for information extraction and target recognition in PET-CT images. The existing detection method cannot meet the requirement of liver recognition in PET-CT images, which is the key problem in the big data analysis of PET-CT images. A novel texture feature descriptor called multi-layer cube sampling (MLCS) is developed for liver boundary detection in low-dose CT and PET images...
June 2018: Australasian Physical & Engineering Sciences in Medicine
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