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The Degree of Skin Burns Images Recognition using Convolutional Neural Network

Hai Son Tran, Thai Hoang Le, Thuy Thanh Nguyen
2016 Indian Journal of Science and Technology  
In recent years, Convolutional Neural Network (CNN) model is the stat of art model successful for image analysis.  ...  The aim of this paper is to build to automated computer aided for identifying the degrees of burn images.  ...  Convolution Neural Network (CNN) Apply for Skin Burn Images CNN model for skin burn images works as automatic skin burn wound recognition and computer aided in the burning victims diagnosis. system 4 .  ... 
doi:10.17485/ijst/2016/v9i45/106772 fatcat:fggd7pomzzavjait7z24zav4me

Front Matter: Volume 9785

2016 Medical Imaging 2016: Computer-Aided Diagnosis  
Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model.  ...  These two-number sets start with 00, 01, 02, 03, 04, 05, 06, 07, 08, 09, 0A, 0B ... 0Z, followed by 10-1Z, 20-2Z, etc. The CID Number appears on each page of the manuscript.  ...  network for computer-aided detection of microcalcifications in digital breast tomosynthesis [9785-33] 9785 0Z Computer aided lung cancer diagnosis with deep learning algorithms [9785-34] 9785 10  ... 
doi:10.1117/12.2240961 dblp:conf/micad/X16 fatcat:b5addnksdrgp3ixwvbjt53xeqe

Front Matter: Volume 11597

Karen Drukker, Maciej A. Mazurowski
2021 Medical Imaging 2021: Computer-Aided Diagnosis  
of lung cancer in screening vi Proc. of SPIE Vol. 11597 1159701-6 s), "Title of Paper," in Medical Imaging 2021: Computer-Aided Diagnosis, edited by Maciej A.  ...  non-Parkinsonian olfactory dysfunction with structural MRI data [11597-47] 11597 1F Use of biplane quantitative angiographic imaging with ensemble neural networks to assess reperfusion status during  ...  segmentation of small metastatic brain tumors using liquid state machine ensemble 11597 2M Renal parenchyma segmentation in abdominal MR images based on cascaded deep convolutional neural network with  ... 
doi:10.1117/12.2595447 fatcat:u25cvo7adbgcxb363rsnsgnsju

Artificial Intelligence: The Future in Dentistry

2020 Indian Journal of Forensic Medicine & Toxicology  
These innovations would enable dentists to work with precision in all aspects of diagnosis and treatment planning.  ...  Artificial intelligence (AI) is an area of computer technologies in influencing our lives.  ...  They provide a differential diagnosis for different abnormalities in radio images in various imaging modalities. 7 Thus digital imaging modalities have enabled the usage of Computer-aided diagnosis in  ... 
doi:10.37506/ijfmt.v14i4.12947 fatcat:c25zqx3kpzal7hxqkgqmrcombm

A Survey on Pneumonia Detection Methods Using Computer-aided Diagnosis

2021 International Journal of Emerging Trends in Engineering Research  
Recent advances in computer-assisted identification support the diagnosis of Pneumonia using imaging.  ...  Therefore, there are many activities available for diagnosing pneumonia using Computer-Aided Diagnosis. This paper provides research into the in-depth study strategies used to diagnose pneumonia.  ...  RELATED WORK Much work has already be done in pneumonia detection field by using Computer-aided Diagnosis and the latest improvements in Computer-aided Diagnosis methods allow them to be used in various  ... 
doi:10.30534/ijeter/2021/09972021 fatcat:bqmjdndb3bevjlel4gcqkllbim

Medical image analysis with artificial neural networks

J. Jiang, P. Trundle, J. Ren
2010 Computerized Medical Imaging and Graphics  
Indexing terms: neural networks, medical imaging analysis, and intelligent computing. 2 Neural network applications in computer-aided diagnosis represent the main stream of computational intelligence in  ...  After this section, four sections are organised to provide detailed descriptions of neural network applications in the areas of computer aided diagnosis, image segmentation and edge detection, image registration  ...  Neural Networks for Computer Aided Detection and Diagnosis Neural networks have been incorporated into many computer-aided diagnosis systems, most of which distinguish the cancerous signs from normal tissues  ... 
doi:10.1016/j.compmedimag.2010.07.003 pmid:20713305 fatcat:iycrdoy4yfgjfof2ml4xk7iz6i

Implementing Precision Medicine and Artificial Intelligence in Plastic Surgery

You J. Kim, Brian P. Kelley, Jacob S. Nasser, Kevin C. Chung
2019 Plastic and Reconstructive Surgery, Global Open  
The algorithmic process of artificial neural networks will guide large-scale analysis of data, including features such as pattern recognition and rapid quantification, to organize and distribute data to  ...  Therefore, plastic surgeons must learn how to use AI within the contexts of our practices to keep up with an evolving field in medicine.  ...  will enable surgeons to formulate individualized Furthermore, AI-assisted evaluation of computed tomography (CT) angiograms, along with other smart imaging techniques, could aid surgeons in the design  ... 
doi:10.1097/gox.0000000000002113 pmid:31044104 pmcid:PMC6467615 fatcat:lehuglc7ordprjbqnpauvlcy4q

Deepwound: Automated Postoperative Wound Assessment and Surgical Site Surveillance through Convolutional Neural Networks [article]

Varun Shenoy, Elizabeth Foster, Lauren Aalami, Bakar Majeed, Oliver Aalami
2018 arXiv   pre-print
Convolutional neural networks (CNNs), a subgroup of artificial neural networks that have shown great promise in analyzing visual imagery, can be leveraged to categorize surgical wounds.  ...  Paired with deep neural networks, they offer the capability to provide clinical insight to assist surgeons during postoperative care.  ...  Thus, a rapid and portable computer aided diagnosis (CAD) tool for wound assessment will greatly assist surgeons in determining the status of a wound in a timely manner.  ... 
arXiv:1807.04355v1 fatcat:bftqgsdt4vcbba2o5huec3vjxe

A Study of Performance Evaluation of Convolution Neural Network for Diabetic Retinopathy

Kusuma R C
2020 International Journal of Advanced Trends in Computer Science and Engineering  
Computer-aided verification of fundus images is necessary because it permits for fast processing and bunch images can be analyzed in one shot at a time.  ...  At present diagnosis for the detection of the diabetic retinopathy mainly depends on ophthalmologist who examines the retinal image and decides the patient's condition that they have diabetic retinopathy  ...  The computer-adied technique will effectively aid the Clinicians for diagnosis. So by using this technologies the chances of Misdignosis will be very less whe compared to manual diagnosis.  ... 
doi:10.30534/ijatcse/2020/118942020 fatcat:errcchlo4bdijhzybuy4h44yhm

FASTER–RCNN for Skin Burn Analysis and Tissue Regeneration

C. Pabitha, B. Vanathi
2022 Computer systems science and engineering  
Deep neural networks can automatically assist in the extraction of features from a burn image.  ...  Effective diagnosis with the help of accurate burn zone and wound depth evaluation is important for clinical efficacy.  ...  By providing a cure for skin burn wounds, advancements in the fields of artificial intelligence and computer vision aid in providing a greater solution and faster recoverability.  ... 
doi:10.32604/csse.2022.021086 fatcat:vo2yd4ak3ffqhn4x4e4dpnrtnm

Applications of Explainable Artificial Intelligence in Diagnosis and Surgery

Yiming Zhang, Ying Weng, Jonathan Lund
2022 Diagnostics  
In this review, we conducted a survey of the recent trends in medical diagnosis and surgical applications using XAI.  ...  Additionally, we provide an experimental showcase on breast cancer diagnosis, and illustrate how XAI can be applied in medical XAI applications.  ...  Meldo et al. proposed a lung cancer computer-aided diagnosis system with explanation sentences [37] .  ... 
doi:10.3390/diagnostics12020237 pmid:35204328 pmcid:PMC8870992 fatcat:fk5gbai6szf2vhf222o7p6nkqy

A Review on the Use of Artificial Intelligence in Spinal Diseases

Parisa Azimi, Taravat Yazdanian, Edward C. Benzel, Hossein Nayeb Aghaei, Shirzad Azhari, Sohrab Sadeghi, Ali Montazeri
2020 Asian Spine Journal  
Artificial neural networks (ANNs) have been used in a wide variety of real-world applications and it emerges as a promising field across various branches of medicine.  ...  Our review indicates several applications of ANNs in the management of spinal diseases including (1) diagnosis and assessment of spinal disease progression in the patients with low back pain, perioperative  ...  In conclusion, the computer-aided method has potential for automatic Cobb angle measurement and scoliosis diagnosis on chest X-rays.  ... 
doi:10.31616/asj.2020.0147 pmid:32326672 pmcid:PMC7435304 fatcat:cxdxp3jpurcgzp2hjne5mrj5qu

AN EFFICIENT SKIN CANCER PROGNOSIS STRATEGY USING DEEP LEARNING TECHNIQUES

S. RANGA SWAMY Dr., C. SRINIVASA KUMAR Dr., A. Gauthami Latha Dr.
2021 Indian Journal of Computer Science and Engineering  
In addition, the model not require much computing power to train.  ...  This study provides a model of the Convolutional neural network trained for skin lesion images, from previously acquired features of the Highway Convolutional neural network (CNN).  ...  For instance, neuromuscular neural networks can identify carcinoma [24] . Direct digital imaging is a popular method for medical diagnosis with new computing and device learning mechanisms.  ... 
doi:10.21817/indjcse/2021/v12i1/211201180 fatcat:njcau35yjjge5g6cxuioin4x4u

Segmentation and classification of burn images by color and texture information

Begoña Acha, Carmen Serrano, José I. Acha, Laura M. Roa
2005 Journal of Biomedical Optics  
In this paper, a burn color image segmentation and classification system is proposed.  ...  The neural network classifies burns into three types of burn depths: superficial dermal, deep dermal, and full thickness.  ...  Torre, and the burn unit of Virgen del Rocío Hospital, Seville ͑Spain͒ for providing us with the burn wound photographs and their medical advice, and the CICYT Spain ͑Project No.  ... 
doi:10.1117/1.1921227 pmid:16229658 fatcat:monpwvaj7nexxbwoscdzvbhyza

Burn image segmentation based on Mask Regions with Convolutional Neural Network deep learning framework: more accurate and more convenient

Chong Jiao, Kehua Su, Weiguo Xie, Ziqing Ye
2019 Burns & Trauma  
Moreover, this framework just needs a suitable burn wound image when analyzing the burn wound. It is more convenient and more suitable when using in clinics compared with the traditional methods.  ...  We designed this deep learning segmentation framework based on the Mask Regions with Convolutional Neural Network (Mask R-CNN).  ...  Availability of data and materials The data used in this study cannot be shared in compliance with Wuhan 607 Hospital NO.3 ethics and confidentiality.  ... 
doi:10.1186/s41038-018-0137-9 pmid:30859107 pmcid:PMC6394103 fatcat:umadn2wfjncsnpwxgraqbkai3i
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