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Image processing techniques for cancer classification

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https://read.qxmd.com/read/30755214/a-pap-smear-analysis-tool-pat-for-detection-of-cervical-cancer-from-pap-smear-images
#1
Wasswa William, Andrew Ware, Annabella Habinka Basaza-Ejiri, Johnes Obungoloch
BACKGROUND: Cervical cancer is preventable if effective screening measures are in place. Pap-smear is the commonest technique used for early screening and diagnosis of cervical cancer. However, the manual analysis of the pap-smears is error prone due to human mistake, moreover, the process is tedious and time-consuming. Hence, it is beneficial to develop a computer-assisted diagnosis tool to make the pap-smear test more accurate and reliable. This paper describes the development of a tool for automated diagnosis and classification of cervical cancer from pap-smear images...
February 12, 2019: Biomedical Engineering Online
https://read.qxmd.com/read/30746555/ecm-csd-an-efficient-classification-model-for-cancer-stage-diagnosis-in-ct-lung-images-using-fcm-and-svm-techniques
#2
M S Kavitha, J Shanthini, R Sabitha
As is eminent, lung cancer is one of the death frightening syndromes among people in present cases. The earlier diagnosis and treatment of lung cancer can increase the endurance rate of the affected people. But, the structure of the cancer cell makes the diagnosis process more challenging, in which the most of the cells are superimposed. By adopting the efficient image processing techniques, the diagnosis process can be made effective, earlier and accurate, where the time aspect is extremely decisive. With those considerations, the main objective of this work is to propose a region based Fuzzy C-Means Clustering (FCM) technique for segmenting the lung cancer region and the Support Vector Machine (SVM) based classification for diagnosing the cancer stage, which helps in clinical practice in significant way to increase the morality rate...
February 12, 2019: Journal of Medical Systems
https://read.qxmd.com/read/30735784/a-novel-texture-extraction-technique-with-t1-weighted-mri-for-the-classification-of-alzheimer-s-disease
#3
V Krishnakumar, Latha Parthiban
BACKGROUND: As the medical images contain both superficial and imperceptible patterns, textures are successfully used as discriminant features for the detection of cancers, tumors, etc. NEW METHOD: Our algorithm selects the specific image blocks and computes the textures using the following steps: At first, the center image slice of the axes (sagittal, coronal and axial) is divided into small blocks and those which approximately resembles the regions of interest are marked. Then, all the marked blocks which are in the same location as in the center slice are collected from all the other slices, and the textures are computed per block on all the individual slices...
February 5, 2019: Journal of Neuroscience Methods
https://read.qxmd.com/read/30719560/spotting-malignancies-from-gastric-endoscopic-images-using-deep-learning
#4
Jang Hyung Lee, Young Jae Kim, Yoon Woo Kim, Sungjin Park, Youn-I Choi, Yoon Jae Kim, Dong Kyun Park, Kwang Gi Kim, Jun-Won Chung
BACKGROUND: Gastric cancer is a common kind of malignancies, with yearly occurrences exceeding one million worldwide in 2017. Typically, ulcerous and cancerous tissues develop abnormal morphologies through courses of progression. Endoscopy is a routinely adopted means for examination of gastrointestinal tract for malignancy. Early and timely detection of malignancy closely correlate with good prognosis. Repeated presentation of similar frames from gastrointestinal tract endoscopy often weakens attention for practitioners to result in true patients missed out to incur higher medical cost and unnecessary morbidity...
February 4, 2019: Surgical Endoscopy
https://read.qxmd.com/read/30697861/cloud-based-decision-support-system-for-the-detection-and-classification-of-malignant-cells-in-breast-cancer-using-breast-cytology-images
#5
Tanzila Saba, Sana Ullah Khan, Naveed Islam, Naveed Abbas, Amjad Rehman, Nadeem Javaid, Adeel Anjum
The advancement of computer- and internet-based technologies has transformed the nature of services in healthcare by using mobile devices in conjunction with cloud computing. The classical phenomenon of patient-doctor diagnostics is extended to a more robust advanced concept of E-health, where remote online/offline treatment and diagnostics can be performed. In this article, we propose a framework which incorporates a cloud-based decision support system for the detection and classification of malignant cells in breast cancer, while using breast cytology images...
January 29, 2019: Microscopy Research and Technique
https://read.qxmd.com/read/30678428/active-contour-based-segmentation-and-classification-for-pleura-diseases-based-on-otsu%C3%A2-s-thresholding-and-support-vector-machine-svm
#6
M Malathi, P Sinthia, K Jalaldeen
Objective: Generally, lung cancer is the abnormal growth of cells that originates in one or both lungs. Finding the pulmonary nodule helps in the diagnosis of lung cancer in early stage and also increase the lifetime of the individual. Accurate segmentation of normal and abnormal portion in segmentation is challenging task in computer-aided diagnostics. Methods: The article proposes an innovative method to spot the cancer portion using Otsu’s segmentation algorithm. It is followed by a Support Vector Machine (SVM) classifier to classify the abnormal portion of the lung image...
January 25, 2019: Asian Pacific Journal of Cancer Prevention: APJCP
https://read.qxmd.com/read/30655633/multidisciplinary-approach-to-prostatitis
#7
Vittorio Magri, Matteo Boltri, Tommaso Cai, Roberto Colombo, Salvatore Cuzzocrea, Pieter De Visschere, Rosanna Giuberti, Clara Maria Granatieri, Maria Agnese Latino, Gaetano Larganà, Christian Leli, Giorgio Maierna, Valentina Marchese, Elisabetta Massa, Alberto Matteelli, Emanuele Montanari, Giuseppe Morgia, Kurt G Naber, Vaia Papadouli, Gianpaolo Perletti, Nektaria Rekleiti, Giorgio I Russo, Alessandra Sensini, Konstantinos Stamatiou, Alberto Trinchieri, Florian M E Wagenlehner
The modern clinical research on prostatitis started with the work of Stamey and coworkers who developed the basic principles we are still using. They established the segmented culture technique for localizing the infections in the males to the urethra, the bladder, or the prostate and to differentiate the main categories of prostatitis. Such categories with slight modifications are still used according to the NIH classification: acute bacterial prostatitis, chronic bacterial prostatitis, Chronic Pelvic Pain Syndrome (CPPS) and asymptomatic prostatitis...
January 18, 2019: Archivio Italiano di Urologia, Andrologia
https://read.qxmd.com/read/30652593/automated-renal-cancer-grading-using-nuclear-pleomorphic-patterns
#8
Daniel Aitor Holdbrook, Malay Singh, Yukti Choudhury, Emarene Mationg Kalaw, Valerie Koh, Hui Shan Tan, Ravindran Kanesvaran, Puay Hoon Tan, John Yuen Shyi Peng, Min-Han Tan, Hwee Kuan Lee
PURPOSE: Nuclear pleomorphic patterns are essential for Fuhrman grading of clear cell renal cell carcinoma (ccRCC). Manual observation of renal histopathologic slides may lead to subjective and inconsistent assessment between pathologists. An automated, image-based system that classifies ccRCC slides by quantifying nuclear pleomorphic patterns in an objective and consistent interpretable fashion can aid pathologists in histopathologic assessment. METHODS: In the current study, histopathologic tissue slides of 59 patients with ccRCC who underwent surgery at Singapore General Hospital were assembled retrospectively...
December 2018: JCO Clinical Cancer Informatics
https://read.qxmd.com/read/30651131/hyperspectral-cell-sociology-reveals-spatial-tumor-immune-cell-interactions-associated-with-lung-cancer-recurrence
#9
Katey S S Enfield, Spencer D Martin, Erin A Marshall, Sonia H Y Kung, Paul Gallagher, Katy Milne, Zhaoyang Chen, Brad H Nelson, Stephen Lam, John C English, Calum E MacAulay, Wan L Lam, Martial Guillaud
BACKGROUND: The tumor microenvironment (TME) is a complex mixture of tumor epithelium, stroma and immune cells, and the immune component of the TME is highly prognostic for tumor progression and patient outcome. In lung cancer, anti-PD-1 therapy significantly improves patient survival through activation of T cell cytotoxicity against tumor cells. Direct contact between CD8+ T cells and target cells is necessary for CD8+ T cell activity, indicating that spatial organization of immune cells within the TME reflects a critical process in anti-tumor immunity...
January 16, 2019: Journal for Immunotherapy of Cancer
https://read.qxmd.com/read/30644947/deep-learning-for-ftir-histology-leveraging-spatial-and-spectral-features-with-convolutional-neural-networks
#10
Sebastian Berisha, Mahsa Lotfollahi, Jahandar Jahanipour, Ilker Gurcan, Michael Walsh, Rohit Bhargava, Hien Van Nguyen, David Mayerich
Current methods for cancer detection rely on tissue biopsy, chemical labeling/staining, and examination of the tissue by a pathologist. Though these methods continue to remain the gold standard, they are non-quantitative and susceptible to human error. Fourier transform infrared (FTIR) spectroscopic imaging has shown potential as a quantitative alternative to traditional histology. However, identification of histological components requires reliable classification based on molecular spectra, which are susceptible to artifacts introduced by noise and scattering...
January 15, 2019: Analyst
https://read.qxmd.com/read/30612188/an-enhancement-of-computer-aided-approach-for-colon-cancer-detection-in-wce-images-using-roi-based-color-histogram-and-svm2
#11
P Shanmuga Sundaram, N Santhiyakumari
The colon cancer is formed by uncontrollable growth of abnormal cells in large intestine or colon that can affect both men and women and it is third cancer disease in the world. At present, Wireless Capsule Endoscopy (WCE) screening method is utilized to identify colon cancer tumor at early stage to save the patient life who affected by the colon cancer. In this CTC method, the radiologist needs to analyze the colon polyps in digital image using computer aided approach with accurate automatic tumor classification to detect the cancer tumor at early stage...
January 5, 2019: Journal of Medical Systems
https://read.qxmd.com/read/30565298/defining-clinically-significant-prostate-cancer-on-the-basis-of-pathological-findings
#12
REVIEW
Andres Matoso, Jonathan I Epstein
The definition of clinically significant prostate cancer is a dynamic process that was initiated many decades ago, when there was already evidence that a great proportion of patients with prostate cancer diagnosed at autopsy never had any clinical symptoms. Autopsy studies led to examinations of radical prostatectomy (RP) specimens and the establishment of the definition of significant cancer at RP: tumour volume of 0.5 cm3 , Gleason grade 6 [Grade Group (GrG) 1], and organ-confined disease. RP studies were then used to develop prediction models for significant cancer by the use of needle biopsies...
January 2019: Histopathology
https://read.qxmd.com/read/30392052/mixture-model-segmentation-system-for-parasagittal-meningioma-brain-tumor-classification-based-on-hybrid-feature-vector
#13
L Arokia Jesu Prabhu, A Jayachandran
Meningioma is the one of the most common type of brain tumor, it as arises from the meninges and encloses the spine and the brain inside the skull. It accounts for 30% of all types of brain tumor. Meningioma's can occur in many parts of the brain and accordingly it is named. In this paper, a mixture model based classification of meningioma brain tumor using MRI image is developed. The proposed method consists of four stages. In the first stage, with respect to the cells' boundary, it is necessary to further processing, which ensures the boundary of some cells is a discrete region...
November 3, 2018: Journal of Medical Systems
https://read.qxmd.com/read/30387753/large-scale-multi-class-image-based-cell-classification-with-deep-learning
#14
Nan Meng, Edmund Lam, Kevin Kin Man Tsia, Hayden Kwok-Hay So
Recent advances in ultra-high-throughput optical microscopy have enabled a new generation of cell classification methodologies using image-based cell phenotypes alone. In contrast to the current single-cell analysis techniques that rely solely on slow and costly genetic/epigenetic analyses, these image-based classification methods allow morphological profiling and screening of thousands or even millions of single cells at a fraction of the cost. Furthermore, they have demonstrated the statistical significance required for understanding the role of cell heterogeneity in diverse biological applications, ranging from cancer screening to drug candidate identification/validation processes...
October 31, 2018: IEEE Journal of Biomedical and Health Informatics
https://read.qxmd.com/read/30363524/entering-an-era-of-radiogenomics-in-prostate-cancer-risk-stratification
#15
REVIEW
Nachiketh Soodana-Prakash, Radka Stoyanova, Abhishek Bhat, Maria C Velasquez, Omer E Kineish, Alan Pollack, Dipen J Parekh, Sanoj Punnen
Radiogenomics is a field that amalgamates data from genomics and imaging techniques in order to derive clinically meaningful trends. In this article, we discuss the importance of prostate cancer risk classification and how data derived from genomic testing and multi-parametric magnetic resonance imaging (mpMRI) can be integrated into clinical decision-making processes with a focus on active surveillance (AS). Finally, we describe an ongoing prospective trial (Miami MAST trial) which incorporates imaging (mpMRI) and radiomics data in patients who are on AS for prostate cancer...
September 2018: Translational Andrology and Urology
https://read.qxmd.com/read/30337080/fast-unsupervised-nuclear-segmentation-and-classification-scheme-for-automatic-allred-cancer-scoring-in-immunohistochemical-breast-tissue-images
#16
Aymen Mouelhi, Hana Rmili, Jaouher Ben Ali, Mounir Sayadi, Raoudha Doghri, Karima Mrad
BACKGROUND AND OBJECTIVE: This paper presents an improved scheme able to perform accurate segmentation and classification of cancer nuclei in immunohistochemical (IHC) breast tissue images in order to provide quantitative evaluation of estrogen or progesterone (ER/PR) receptor status that will assist pathologists in cancer diagnostic process. METHODS: The proposed segmentation method is based on adaptive local thresholding and an enhanced morphological procedure, which are applied to extract all stained nuclei regions and to split overlapping nuclei...
October 2018: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/30256567/aiding-the-digital-mammogram-for-detecting-the-breast-cancer-using-shearlet-transform-and-neural-network
#17
Shenbagavalli P, Thangarajan R
Objective: Breast Cancer is the most invasive disease and fatal disease next to lung cancer in human. Early detection of breast cancer is accomplished by X-ray mammography. Mammography is the most effective and efficient technique used for detection of breast cancer in women and also to improve the breast cancer prognosis. The numbers of images need to be examined by the radiologists, the resulting may be misdiagnosis due to human errors by visual Fatigue. In order to avoid human errors, Computer Aided Diagnosis is implemented...
September 26, 2018: Asian Pacific Journal of Cancer Prevention: APJCP
https://read.qxmd.com/read/30245540/tumor-margin-classification-of-head-and-neck-cancer-using-hyperspectral-imaging-and-convolutional-neural-networks
#18
Martin Halicek, James V Little, Xu Wang, Mihir Patel, Christopher C Griffith, Amy Y Chen, Baowei Fei
One of the largest factors affecting disease recurrence after surgical cancer resection is negative surgical margins. Hyperspectral imaging (HSI) is an optical imaging technique with potential to serve as a computer aided diagnostic tool for identifying cancer in gross ex-vivo specimens. We developed a tissue classifier using three distinct convolutional neural network (CNN) architectures on HSI data to investigate the ability to classify the cancer margins from ex-vivo human surgical specimens, collected from 20 patients undergoing surgical cancer resection as a preliminary validation group...
February 2018: Proceedings of SPIE
https://read.qxmd.com/read/30153334/prostate-lesion-delineation-from-multiparametric-magnetic-resonance-imaging-based-on-locality-alignment-discriminant-analysis
#19
Mingquan Lin, Weifu Chen, Mingbo Zhao, Eli Gibson, Matthew Bastian-Jordan, Derek W Cool, Zahra Kassam, Huageng Liang, Tommy W S Chow, Aaron D Ward, Bernard Chiu
PURPOSE: Multiparametric MRI (mpMRI) has shown promise in the detection and localization of prostate cancer foci. Although techniques have been previously introduced to delineate lesions from mpMRI, these techniques were evaluated in datasets with T2 maps available. The generation of T2 map is not included in the clinical prostate mpMRI consensus guidelines; the acquisition of which requires repeated T2-weighted (T2W) scans and would significantly lengthen the scan time currently required for the clinically recommended acquisition protocol, which includes T2W, diffusion-weighted (DW), and dynamic contrast-enhanced (DCE) imaging...
October 2018: Medical Physics
https://read.qxmd.com/read/30051247/classification-of-tumor-epithelium-and-stroma-by-exploiting-image-features-learned-by-deep-convolutional-neural-networks
#20
Yue Du, Roy Zhang, Abolfazl Zargari, Theresa C Thai, Camille C Gunderson, Katherine M Moxley, Hong Liu, Bin Zheng, Yuchen Qiu
The tumor-stroma ratio (TSR) reflected on hematoxylin and eosin (H&E)-stained histological images is a potential prognostic factor for survival. Automatic image processing techniques that allow for high-throughput and precise discrimination of tumor epithelium and stroma are required to elevate the prognostic significance of the TSR. As a variant of deep learning techniques, transfer learning leverages nature-images features learned by deep convolutional neural networks (CNNs) to relieve the requirement of deep CNNs for immense sample size when handling biomedical classification problems...
July 26, 2018: Annals of Biomedical Engineering
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