keyword
MENU ▼
Read by QxMD icon Read
search

Image processing techniques for cancer classification

keyword
https://www.readbyqxmd.com/read/30337080/fast-unsupervised-nuclear-segmentation-and-classification-scheme-for-automatic-allred-cancer-scoring-in-immunohistochemical-breast-tissue-images
#1
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://www.readbyqxmd.com/read/30256567/aiding-the-digital-mammogram-for-detecting-the-breast-cancer-using-shearlet-transform-and-neural-network
#2
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://www.readbyqxmd.com/read/30245540/tumor-margin-classification-of-head-and-neck-cancer-using-hyperspectral-imaging-and-convolutional-neural-networks
#3
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://www.readbyqxmd.com/read/30153334/prostate-lesion-delineation-from-multiparametric-magnetic-resonance-imaging-based-on-locality-alignment-discriminant-analysis
#4
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...
August 28, 2018: Medical Physics
https://www.readbyqxmd.com/read/30051247/classification-of-tumor-epithelium-and-stroma-by-exploiting-image-features-learned-by-deep-convolutional-neural-networks
#5
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
https://www.readbyqxmd.com/read/30050803/magnetic-resonance-imaging-mri-based-radiomics-for-prostate-cancer-radiotherapy
#6
REVIEW
Fei Yang, John C Ford, Nesrin Dogan, Kyle R Padgett, Adrian L Breto, Matthew C Abramowitz, Alan Dal Pra, Alan Pollack, Radka Stoyanova
In radiotherapy (RT) of prostate cancer, dose escalation has been shown to reduce biochemical failure. Dose escalation only to determinate prostate tumor habitats has the potential to improve tumor control with less toxicity than when the entire prostate is dose escalated. Other issues in the treatment of the RT patient include the choice of the RT technique (hypo- or standard fractionation) and the use and length of concurrent/adjuvant androgen deprivation therapy (ADT). Up to 50% of high-risk men demonstrate biochemical failure suggesting that additional strategies for defining and treating patients based on improved risk stratification are required...
June 2018: Translational Andrology and Urology
https://www.readbyqxmd.com/read/29987909/ultrafast-cell-edge-detection-by-line-scan-time-stretch-microscopy
#7
Bo Dai, Lu He, Lulu Zheng, Yongfeng Fu, Kaimin Wang, Guodong Sui, Dawei Zhang, Songlin Zhuang, Xu Wang
Ultrafast time-stretch imaging technique recently attracts an increasing interest for applications in cell classification due to high throughput and high sensitivity. A novel imaging modality of time-stretch imaging technique for edge detection is proposed. Edge detection based on the directional derivative is realized using differential detection. As the image processing is mainly implemented in the physical layer, the computation complexity of edge extraction is significantly reduced. An imaging system for edge detection with the scan rate of 77...
July 10, 2018: Journal of Biophotonics
https://www.readbyqxmd.com/read/29790102/classification-of-malignant-and-benign-lung-nodules-using-taxonomic-diversity-index-and-phylogenetic-distance
#8
Robherson Wector de Sousa Costa, Giovanni Lucca França da Silva, Antonio Oseas de Carvalho Filho, Aristófanes Corrêa Silva, Anselmo Cardoso de Paiva, Marcelo Gattass
Lung cancer presents the highest cause of death among patients around the world, in addition of being one of the smallest survival rates after diagnosis. Therefore, this study proposes a methodology for diagnosis of lung nodules in benign and malignant tumors based on image processing and pattern recognition techniques. Mean phylogenetic distance (MPD) and taxonomic diversity index (Δ) were used as texture descriptors. Finally, the genetic algorithm in conjunction with the support vector machine were applied to select the best training model...
November 2018: Medical & Biological Engineering & Computing
https://www.readbyqxmd.com/read/29720361/automated-modular-magnetic-resonance-imaging-clinical-decision-support-system-miror-an-application-in-pediatric-cancer-diagnosis
#9
Niloufar Zarinabad, Emma M Meeus, Karen Manias, Katharine Foster, Andrew Peet
BACKGROUND: Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. OBJECTIVE: The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data...
May 2, 2018: JMIR Medical Informatics
https://www.readbyqxmd.com/read/29700105/lung-cancer-staging-a-concise-update
#10
Ramón Rami-Porta, Sergi Call, Christophe Dooms, Carme Obiols, Marcelo Sánchez, William D Travis, Ivan Vollmer
Diagnosis and clinical staging of lung cancer are fundamental to planning therapy. The techniques for clinical staging, i.e anatomic and metabolic imaging, endoscopies and minimally invasive surgical procedures, should be performed sequentially and with an increasing degree of invasiveness. Intraoperative staging, assessing the magnitude of the primary tumour, the involved structures, and the loco-regional lymphatic spread by means of systematic nodal dissection, is essential in order to achieve a complete resection...
May 2018: European Respiratory Journal: Official Journal of the European Society for Clinical Respiratory Physiology
https://www.readbyqxmd.com/read/29544146/automatic-classification-of-tissue-malignancy-for-breast-carcinoma-diagnosis
#11
Irene Fondón, Auxiliadora Sarmiento, Ana Isabel García, María Silvestre, Catarina Eloy, António Polónia, Paulo Aguiar
Breast cancer is the second leading cause of cancer death among women. Its early diagnosis is extremely important to prevent avoidable deaths. However, malignancy assessment of tissue biopsies is complex and dependent on observer subjectivity. Moreover, hematoxylin and eosin (H&E)-stained histological images exhibit a highly variable appearance, even within the same malignancy level. In this paper, we propose a computer-aided diagnosis (CAD) tool for automated malignancy assessment of breast tissue samples based on the processing of histological images...
May 1, 2018: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/29428071/detection-of-mass-regions-in-mammograms-by-bilateral-analysis-adapted-to-breast-density-using-similarity-indexes-and-convolutional-neural-networks
#12
João Otávio Bandeira Diniz, Pedro Henrique Bandeira Diniz, Thales Levi Azevedo Valente, Aristófanes Corrêa Silva, Anselmo Cardoso de Paiva, Marcelo Gattass
BACKGROUND AND OBJECTIVE: The processing of medical image is an important tool to assist in minimizing the degree of uncertainty of the specialist, while providing specialists with an additional source of detect and diagnosis information. Breast cancer is the most common type of cancer that affects the female population around the world. It is also the most deadly type of cancer among women. It is the second most common type of cancer among all others. The most common examination to diagnose breast cancer early is mammography...
March 2018: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/29200686/an-investigation-of-bayes-algorithm-and-neural-networks-for-identifying-the-breast-cancer
#13
E Udayakumar, S Santhi, P Vetrivelan
Context: Breast cancer is a biggest threat to women. X-ray mammography is the most effective method for early detection and screening of breast cancer. It is a tough challenge for the radiologist in reading mammography since it does not provide consistent result every time. Aim: To improve the primary sign of this disease, computer-aided diagnosis schemes have been developed. Using monitor, digital images of mammography are displayed and they can be lightened or darkened before they are printed on the film...
July 2017: Indian Journal of Medical and Paediatric Oncology
https://www.readbyqxmd.com/read/29172292/detection-of-juxtapleural-nodules-in-lung-cancer-cases-using-an-optimal-critical-point-selection-algorithm
#14
S Saraswathi, L Mary Immaculate Sheela
Detection of lung cancer through image processing is an important tool for diagnosis. In recent years, image processing techniques have become more widely used. Lung segmentation is an essential pre-processing step for most (CAD) schemes. An automated system is proposed in this paper for identifying lung cancer from the analysis of computed tomography images by performing nodule segmentation using an optimal critical point selection algorithm (OCPS) which improves the detection of shape- and size-based juxtapleural nodules located at the lung boundary...
November 26, 2017: Asian Pacific Journal of Cancer Prevention: APJCP
https://www.readbyqxmd.com/read/29018612/segmentation-and-classification-of-colon-glands-with-deep-convolutional-neural-networks-and-total-variation-regularization
#15
Philipp Kainz, Michael Pfeiffer, Martin Urschler
Segmentation of histopathology sections is a necessary preprocessing step for digital pathology. Due to the large variability of biological tissue, machine learning techniques have shown superior performance over conventional image processing methods. Here we present our deep neural network-based approach for segmentation and classification of glands in tissue of benign and malignant colorectal cancer, which was developed to participate in the GlaS@MICCAI2015 colon gland segmentation challenge. We use two distinct deep convolutional neural networks (CNN) for pixel-wise classification of Hematoxylin-Eosin stained images...
2017: PeerJ
https://www.readbyqxmd.com/read/28911905/gaussian-process-classification-of-superparamagnetic-relaxometry-data-phantom-study
#16
Javad Sovizi, Kelsey B Mathieu, Sara L Thrower, Wolfgang Stefan, John D Hazle, David Fuentes
MOTIVATION: Superparamagnetic relaxometry (SPMR) is an emerging technology that holds potential for use in early cancer detection. Measurement of the magnetic field after the excitation of cancer-bound superparamagnetic iron oxide nanoparticles (SPIONs) enables the reconstruction of SPIONs spatial distribution and hence tumor detection. However, image reconstruction often requires solving an ill-posed inverse problem that is computationally challenging and sensitive to measurement uncertainty...
October 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/28884120/automated-classification-of-lung-cancer-types-from-cytological-images-using-deep-convolutional-neural-networks
#17
Atsushi Teramoto, Tetsuya Tsukamoto, Yuka Kiriyama, Hiroshi Fujita
Lung cancer is a leading cause of death worldwide. Currently, in differential diagnosis of lung cancer, accurate classification of cancer types (adenocarcinoma, squamous cell carcinoma, and small cell carcinoma) is required. However, improving the accuracy and stability of diagnosis is challenging. In this study, we developed an automated classification scheme for lung cancers presented in microscopic images using a deep convolutional neural network (DCNN), which is a major deep learning technique. The DCNN used for classification consists of three convolutional layers, three pooling layers, and two fully connected layers...
2017: BioMed Research International
https://www.readbyqxmd.com/read/28778512/ct-image-based-decision-support-system-for-categorization-of-liver-metastases-into-primary-cancer-sites-initial-results
#18
Avi Ben-Cohen, Eyal Klang, Idit Diamant, Noa Rozendorn, Stephen P Raskin, Eli Konen, Michal Marianne Amitai, Hayit Greenspan
RATIONALE AND OBJECTIVES: This study aimed to provide decision support for the human expert, to categorize liver metastases into their primary cancer sites. Currently, once a liver metastasis is detected, the process of finding the primary site is challenging, time-consuming, and requires multiple examinations. The proposed system can support the human expert in localizing the search for the cancer source by prioritizing the examinations to probable cancer sites. MATERIALS AND METHODS: The suggested method is a learning-based approach, using computed tomography (CT) data as the input source...
December 2017: Academic Radiology
https://www.readbyqxmd.com/read/28555888/computerized-detection-of-leukocytes-in-microscopic-leukorrhea-images
#19
Jing Zhang, Ya Zhong, Xiangzhou Wang, Guangming Ni, Xiaohui Du, Juanxiu Liu, Lin Liu, Yong Liu
PURPOSE: Detection of leukocytes is critical for the routine leukorrhea exam, which is widely used in gynecological examinations. An elevated vaginal leukocyte count in women with bacterial vaginosis is a strong predictor of vaginal or cervical infections. In the routine leukorrhea exam, the counting of leukocytes is primarily performed by manual techniques. However, the viewing and counting of leukocytes from multiple high-power viewing fields on a glass slide under a microscope leads to subjectivity, low efficiency, and low accuracy...
September 2017: Medical Physics
https://www.readbyqxmd.com/read/28526968/computer-aided-diagnosis-of-lung-nodules-in-computed-tomography-by-using-phylogenetic-diversity-genetic-algorithm-and-svm
#20
Antonio Oseas de Carvalho Filho, Aristófanes Corrêa Silva, Anselmo Cardoso de Paiva, Rodolfo Acatauassú Nunes, Marcelo Gattass
Lung cancer is pointed as the major cause of death among patients with cancer throughout the world. This work is intended to develop a methodology for diagnosis of lung nodules using images from the Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). The proposed methodology uses image processing and pattern recognition techniques. In order to differentiate between the patterns of malignant and benign nodules, we used phylogenetic diversity by means of particular indexes, that are: intensive quadratic entropy, extensive quadratic entropy, average taxonomic distinctness, total taxonomic distinctness, and pure diversity indexes...
December 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
keyword
keyword
167542
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"