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Improving polyp detection algorithms for CT colonography: Pareto front approach

Adam Huang, Jiang Li, Ronald M. Summers, Nicholas Petrick, Amy K. Hara
2010 Pattern Recognition Letters  
A dataset of 56 CTC colon surfaces with 87 proven positive detections of 53 polyps sized 4 to 60 mm was used to evaluate the performance of a one-step and a two-step curvature-based region growing algorithm  ...  We investigated a Pareto front approach to improving polyp detection algorithms for CT colonography (CTC).  ...  This additional figure adds clarity to our discussion and leads us to correct an error in the operating parameter N B value given in ).  ... 
doi:10.1016/j.patrec.2010.03.013 pmid:20548966 pmcid:PMC2883789 fatcat:z4clxgx2ojbrte7v4k5bjwpulm

Issue Information

2021 International journal of imaging systems and technology (Print)  
In addition to performing mundane tasks, imaging systems allow us to study astronomical objects and molecules; they are widely used in quality control and oil exploration.  ...  Remarkably, the same principles are used to build non-invasive tools for studying the anatomy and physiology of various human and animal organs, including the most complex one, the brain.  ...  launching the initiative, we have focused on sharing our content with those in need, enhancing community philanthropy, reducing our carbon impact, creating global guidelines and best practices for paper use  ... 
doi:10.1002/ima.22449 fatcat:r2ym52iidneirfyqo4vl43roi4

Ensembles of Deep Learning Framework for Stomach Abnormalities Classification

Talha Saeed, Chu Kiong Loo, Muhammad Shahreeza Safiruz Kassim
2022 Computers Materials & Continua  
Secondly, XAI techniques are used to interpret which part of the images CNN takes for feature extraction.  ...  Hence, Explainable Artificial Intelligence (XAI) techniques are applied to overcome this issue by interpreting the decisions of the CNNs in such wise the physicians can trust.  ...  In [6] , the author proposed a deep CNN features-based technique and afterward selected optimal features through DE evolutionary algorithm.  ... 
doi:10.32604/cmc.2022.019076 fatcat:cx2qs3rzgrhrlobc47tbd4ovhu

Feature selection for RFID tag identification

D. Banerjee, Jiang Li, Jia Di, D. R. Thompson
2012 7th International Conference on Communications and Networking in China  
We present a multi-objective optimization (MOOP) based feature selection technique for radio frequency identification (RFID) where a tag is identified by matching a set of unique characteristics measured  ...  Experiment results show that the proposed technique can provide a broad view of the effectiveness of the system permitting a system designer to meet specific security requirements for a given application  ...  We have done a similar work for a computer-aided colon polyp detection system [9] . In the optimization procedure, any distance measure can be used.  ... 
doi:10.1109/chinacom.2012.6417479 dblp:conf/chinacom/BanerjeeLDT12 fatcat:5oc24kbssnb63acjieosvfps4u

Convolutional neural networks in medical image understanding: a survey

D. R. Sarvamangala, Raghavendra V. Kulkarni
2021 Evolutionary Intelligence  
Imaging techniques are used to capture anomalies of the human body. The captured images must be understood for diagnosis, prognosis and treatment planning of the anomalies.  ...  The major medical image understanding tasks, namely image classification, segmentation, localization and detection have been introduced.  ...  , FC with adaboost Retinopathy Segmentation (Conv, ReLu, maxpool) ×10 , 3 FC, softmax classifier Colon Polyp Classification Any simple CNN architecture Polyp Detection Ensemble of CNN Skin Melanoma  ... 
doi:10.1007/s12065-020-00540-3 pmid:33425040 pmcid:PMC7778711 fatcat:ykdwhdv3pzfqpnueyieinxofie

Biomedical Imaging: Past, Present and Predictions

Richard A. ROBB, Richard A. ROBB
2006 Medical Imaging Technology  
Figure 22 shows an example of virtual colonoscopy -endoscopic views within the colon computed from a fast spiral CT scan of the abdomen of a patient with colonic polyps.  ...  Traversing the distances between these virtual objects and appropriately scaling their local environment to relevant dimensions will be automatic and instantaneous.  ... 
doi:10.11409/mit.24.25 fatcat:js4jhvdznnb3jm735ridznuhqy

Deep Learning Based Pain Treatment

Tarun Jaiswal, Sushma Jaiswal
2019 International Journal of Trend in Scientific Research and Development  
This discipline uses Computational processing of difficult pain-associated records and relies on "intelligent" Machine learning algorithms.  ...  The current review objectives to familiarize pain area professionals with the methods and current applications of machine learning in pain investigation, possibly simplifying the awareness of the methods  ...  , 176 patients for lymph node detection, and 1,186 patients for colonic polyp detection.  ... 
doi:10.31142/ijtsrd23639 fatcat:tqg4u3tkgjhmjpya67g3lnewwu

Evolving Concepts of Food Safety: The Need for Understanding Mechanisms of Food Toxicology for Public Policy

2018 Advances in Nutrition & Food Science  
The objective of this "Communication" is to integrate a shared underlying mechanism of toxicity between acute and chronic diseases.  ...  While the predominant and legitimate concern is to detect and eliminate microbial pathogens that can cause acute illnesses and deaths (estimated 3-5 thousand deaths in the United States and millions of  ...  Food Safety's Role in Human Carcinogenesis: Dietary Modulation of the Multi-Stage, Multi-Mechanisms of Human Carcinogenesis: Effects On Initiated Stem Cells and Cell-Cell Communication Using human cancer  ... 
doi:10.33140/anfs/03/02/0010 fatcat:mzj6dgspzfaldlvu26b6hv7qh4

Towards the Virtual Physiological Human [article]

Nadia Magnenat-Thalmann, Benjamin Gilles, Hervé Delingette, Andrea Giachetti, Marco Agus
2007 Eurographics State of the Art Reports  
Human body representations have been used for centuries to help in understanding and documenting the shape and function of its compounding parts.  ...  The objective of this tutorial is to train students and researchers in the various domains involving the modelling and simulation of the human body for medical purposes.  ...  For example, to remove false detection of fecal residuals as polyps a recent technique consists of using a translucent rendering mapping colors related to the density over the colon walls, reducing the  ... 
doi:10.2312/egt.20071062 fatcat:iyybqfp4nnadhfkaeagp6qr63q

Health in Digital World: A Regulatory Overview in United States

Ashutosh Mishra, M. P. Gowrav, V. Balamuralidhara, Kolli Suhas Reddy
2021 Journal of Pharmaceutical Research International  
Different regulatory authorities like China, Europe, and United States (US) have adopted AI for economic and policy aspects. Emerging countries are using these tools for administrative work.  ...  This review article provides a snapshot of AI implementation in pharmaceuticals and health care with the regulatory approach in the US.  ...  Fuzzy logic, ML ,Big data analysis, Game theory and multi-agent systems, Simulation (Digital modelling), Evolutionary/bionic algorithms, Expert systems, and DSS (decisionsupport systems) tools can be applied  ... 
doi:10.9734/jpri/2021/v33i43b32573 fatcat:onfhzmgpzvhezeujf4t45gucue

Medical Image Segmentation Using Deep Learning: A Survey [article]

Risheng Wang, Tao Lei, Ruixia Cui, Bingtao Zhang, Hongying Meng, Asoke K. Nandi
2021 arXiv   pre-print
In this paper, we present a comprehensive thematic survey on medical image segmentation using deep learning techniques. This paper makes two original contributions.  ...  directly divide literatures of deep learning on medical image segmentation into many groups and introduce literatures in detail for each group, we classify currently popular literatures according to a multi-level  ...  Multi-modality Data Fusion Multi-modality data fusion has been widely used in medical image analysis because it can provide richer object features that are helpful for improving object detection and segmentation  ... 
arXiv:2009.13120v3 fatcat:ntgbqwkz55axrjum72elbm6rry

Medical image segmentation using deep learning: A survey

Risheng Wang, Tao Lei, Ruixia Cui, Bingtao Zhang, Hongying Meng, Asoke K. Nandi
2022 IET Image Processing  
A comprehensive thematic survey on medical image segmentation using deep learning techniques is presented. This paper makes two original contributions.  ...  directly divide literatures of deep learning on medical image segmentation into many groups and introduce literatures in detail for each group, we classify currently popular literatures according to a multi-level  ...  Multi-modality data fusion Multi-modality data fusion has been widely used in medical image analysis because it can provide richer object features that are helpful for improving object detection and segmentation  ... 
doi:10.1049/ipr2.12419 fatcat:zvgj3vdzqbfbzjoglgmtnn6ukq

Graphics, Vision, and Visualization in Medical Imaging: A State of the Art Report [article]

Norberto Ezquerra, Isabel Navazo, Tahia Infantes Morris, Eva Monclus
1999 Eurographics State of the Art Reports  
The overall objective is therefore to provide a "snap shot" of the field through a brief summary that will hopefully serve as a useful source of information for those wanting to learn more about the field  ...  As the title of this paper suggests, one interesting result of this evolutionary process has been the fusion of traditionally disjointed yet highly interrelated areas: from computer vision and image processing  ...  Multi-resolution interactive filtering techniques are used to enhance the images, while semiautomatic segmentation is used for extracting structures of interest [Wal95] .  ... 
doi:10.2312/egst.19991067 fatcat:xb3sv64whrh4vj22a6caleffby

2021 Index IEEE Transactions on Instrumentation and Measurement Vol. 70

2021 IEEE Transactions on Instrumentation and Measurement  
Guo, Y., +, TIM 2021 2506812 Colon Polyp Detection and Segmentation Based on Improved MRCNN.  ...  Baghbani, R., +, TIM 2021 4006407 Colon Polyp Detection and Segmentation Based on Improved MRCNN.  ... 
doi:10.1109/tim.2022.3156705 fatcat:dmqderzenrcopoyipv3v4vh4ry

Prediction of miRNA-disease Associations using an Evolutionary Tuned Latent Semantic Analysis

Denis Pallez, Julien Gardès, Claude Pasquier
2017 Scientific Reports  
In this paper, we focus on the use of Evolutionary Algorithms (EA) to determine, in a reasonable time, a satisfactory tuning without having to evaluate all the possible configurations.  ...  The automatically parametrized version of MiRAI achieved excellent performance.  ...  Detection and correction of mis-annotations.  ... 
doi:10.1038/s41598-017-10065-y pmid:28874691 pmcid:PMC5585369 fatcat:nicflttr45awtcczq5pk3tcksi
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