scholarly journals Classification of Asbestosis in CT Imaging Data Using Convolutional LSTM

2021 ◽  
Author(s):  
Doohyung Kim ◽  
Jun-Pyo Myong ◽  
Sung Won Han
Keyword(s):  
High Rate ◽  
True Positive ◽  
Imaging Data ◽  
True Negative ◽  
Learning Framework ◽  
Ct Data ◽  
Video Format ◽  
Convolutional Lstm

Abstract Asbestosis is a disease with a high rate of mismatch between the readers. In this study, we use a deep learning framework to develop a model that can check the presence and lesion of asbestosis using medical CT data. The data was collected from 469 patients who had been tested for asbestosis. Out of the 469 patients, 284 were tested negative for asbestosis, while 185 were asbestosis positive. A CT image of a supine positioned lung setting was used. This study sought to solve the problem of image classification of CT data through Convolutional LSTM. Long-term Recurrent Convolution Networks (LRCN), a model that uses video format data as input, has been applied in this study. The model showed 83.3% Accuracy, 81.578% true positive and 86% true negative. In addition, a model that can verify validity by assisting a specialist with a Grad-CAM that can visualize the judgment was also developed. We hope that the model of this study will be able to work with specialists by acting as a judgment assistant.

scholarly journals Classification of Micro-Calcification in Breast from Mammographic Images using Transfer Learning

2020 ◽  
Vol 8 (5) ◽  
pp. 4835-4841
Keyword(s):  
Transfer Learning ◽  
Early Identification ◽  
Breast Tumor ◽  
Early Detection Of Cancer ◽  
Medical Images ◽  
Term Survival ◽  
Learning Framework ◽  
Mammographic Images

Early detection of cancer is most important for long term survival of patient. Now a days CADx are widely used for early identification of breast cancer automatically. CAD uses significant features to identify and categorize cancer. CADx based on Convolutional Neural Network are becoming popular now a days due to extracting relevant features automatically. CNNs can be trained from scratch for medical images due to various input sizes and tumor structures. But due to limited amount of medical images available for training ,we have used transfer learning approach.We developed a deep learning framework based on CNN to discriminate the breast tumor either benign or malignant using transfer learning. We used digital mammographic images containing both views from CBIS-DDSM database. We have achived training(100%) and validation accuracy greater than 90% with minimum training and validation loss. We have also compared the reaults with transfer learning using pretrained network alexnet and googlenet on same dataset.

scholarly journals Classification of Cancer of The Lungs Using SVM and ANN

2015 ◽  
Vol 15 (1) ◽  
pp. 6418-6426 ◽  
Author(s):  
Olusayo Deborah Fenwa ◽  
Funmilola A. Ajala ◽  
Adebisi A. Adigun
Keyword(s):  
Lung Diseases ◽  
Human Life ◽  
False Negative ◽  
Accurate Diagnosis ◽  
Lung Nodules ◽  
True Positive ◽  
True Negative ◽  
Diagnosis Of Cancer ◽  
Sensitivity Specificity

Accurate diagnosis of cancer plays an important role in order to save human life. The results of the diagnosis indicate by the medical experts are mostly differentiated based on the experience of different medical experts. This problem could risk the life of the cancer patients. A fast and effective method to detect the lung nodules and separate the cancer images from other lung diseases like tuberculosis is becoming increasingly needed due to the fact that the incidence of lung cancer has risen dramatically in recent years and an early detection can save thousands of lives each year. The focus of this paper is to compare the performance of the ANN and SVM classifiers on acquired online cancer datasets. The performance of both classifiers is evaluated using different measuring parameters namely; accuracy, sensitivity, specificity, true positive, true negative, false positive and false negative.

scholarly journals Application of Absorption and Scattering Properties Obtained through Image Pre-Classification Method Using a Laser Backscattering Imaging System to Detect Kiwifruit Chilling Injury

Foods ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1446
Author(s):  
Zhuo Yang ◽  
Mo Li ◽  
Andrew R. East ◽  
Manuela Zude-Sasse
Keyword(s):  
Classification Accuracy ◽  
Imaging System ◽  
Chilling Injury ◽  
Soluble Solids ◽  
Soluble Solids Content ◽  
True Positive ◽  
Solids Content ◽  
Non Destructive

Kiwifruit chilling injury (CI) damage occurs after long-term exposure to low temperature. A non-destructive approach to detect CI injury was tested in the present study, using a laser backscattering image (LBI) technique calibrated with 56 liquid phantoms for providing absorption coefficient (µa) and reduced scattering coefficient (µs’). Calibration of LBI resulted in a true-positive (TP) classification of 91.5% and 65.6% of predicted µs’ and µa, respectively. The optical properties of ‘SunGold™’and ‘Hayward’ kiwifruit were analysed at 520 nm with a two-step protocol capturing pre-classification according to the LBI parameters used in the calibration and estimation with the Farrell equation. Severely injured kiwifruit showed white corky tissue and water soaking, reduced soluble solids content and firmness measured destructively. Non-destructive classification results for ‘SunGold™’ showed a high percentage of TP for severe CI of 92% and 75% using LBI parameters directly and predicted µa and µs’ after pre-classification, respectively. The classification accuracy for severe CI ‘Hayward’ kiwifruit with LBI parameter was low (58%) and with µa and µs’ decreased further (35%), which was assumed to be due to interference caused by the long trichomes on the fruit surface.

scholarly journals Classification of Melanoma and Nevus for Diagnosis of Skin Cancer by Using Optimized Convolution Neural Network

2021 ◽  
Vol 9 (12) ◽  
pp. 1984-1989
Author(s):  
Neha Maheshwari
Keyword(s):  
Neural Network ◽  
Median Filter ◽  
Confusion Matrix ◽  
False Negative ◽  
Convolution Neural Network ◽  
True Positive ◽  
True Negative ◽  
Index Terms ◽  
Risk Of Cancer

Abstract: Melanoma is taken into account a fatal sort of carcinoma .Differentiating melanoma from nevus is difficult task. Nevus is a common pigmented skin lesion, usually developing during adulthood, which is harmless. Since they look similar it has to be identified and reduce the risk of cancer. The death rate thanks to this disease is in particular other skin-related consolidated malignancies. In this work, we have used convolution neural networks to classify the image into melanoma and nevus. The images are pre-processed using median filter, top-bottom hat filter and are passed through layers of CNN. We have achieved an accuracy of 97.56%, sensitivity of 95.23%.The F1_socre is 97.56. Index terms: Melanoma, Nevus, True Positive, True Negative, False Negative, False Positive, Confusion Matrix, Epoch, Convolution Neural Network.

STUDY ON CLINICAL CHARACTERISTICS AND RESULT OF TREATMENT BENIGN VOCAL CORD TUMOR WITH RIGID LARYNGEAL ENDOSCOPIC SURGERY

2012 ◽  
pp. 58-65
Author(s):  
Duy Thai Truong ◽  
Van Dung Phan ◽  
Tu The Nguyen
Keyword(s):  
Vocal Cord ◽  
Endoscopic Surgery ◽  
Clinical Characteristics ◽  
University Hospital ◽  
High Rate ◽  
Treatment Rate ◽  
Reinke’S Edema ◽  
Vocal Nodules ◽  
A Prospective Study

Objective: Study on clinical characteristics and result of treatment benign vocal cord tumor with suspensive laryngeal endoscopic surgery. Materials and Methods: A prospective study was undertaken in 43 patients who had benign vocal cord tumor and performed a suspensive laryngeal endoscopic surgery at ENT Dept. of Hue University Hospital, from 3/2010 to 5/2011. Results: The most common was group was 31 - 45 (44.2%). There was no difference of gender. Moderate hoarness was 67.4%. Classification of benign laryngeal tumor: vocal nodules (13 cases), vocal cyst (18 cases), vocal polyp (10 cases) and Reinke’s edema (2 cases). The successful treatment rate of vocal benign tumor was 88.4%. Conclusions: Suspensive laryngeal endoscopic surgery was the best method to cure benign vocal cord tumor. The surgeon had a clear operative field, easy manoeuver, high rate of cure and less complication.

MODERN PROBLEMATICS AND ANALYSIS OF EFFICIENCY OF APPLICATION OF DIFFERENT APPROACHES TO DESTRUCTION OF INFORMATION ON MAGNETIC MEDIA

2019 ◽  
Vol 2 (12) ◽  
pp. 154-164
Author(s):  
O. Semenenko ◽  
O. Vodchyts ◽  
V. Koverga ◽  
R. Lukash ◽  
O. Lutsenko
Keyword(s):  
Armed Forces ◽  
Information Storage ◽  
Storage Device ◽  
Magnetic Media ◽  
Long Term Storage ◽  
Physical Impact ◽  
And Storage ◽  
Term Storage

The introduction and active use of information transmission and storage systems in the Ministry of Defense (MoD) of Ukraine form the need to develop ways of guaranteed removal of data from media after their use or long-term storage. Such a task is an essential component of the functioning of any information security system. The article analyzes the problems of guaranteed destruction of information on magnetic media. An overview of approaches to the guaranteed destruction of information on magnetic media of different types is presented, and partial estimates of the effectiveness of their application are given by some generally accepted indicators of performance evaluation. The article also describes the classification of methods of destruction of information depending on the influence on its medium. The results of the analysis revealed the main problems of application of software methods and methods of demagnetization of the information carrier. The issue of guaranteed destruction of information from modern SSD devices, which are actively used in the formation of new systems of information accumulation and processing, became particularly relevant in the article. In today's conditions of development of the Armed Forces of Ukraine, methods of mechanical and thermal destruction are more commonly used today. In the medium term, the vector of the use of information elimination methods will change towards the methods of physical impact by the pulsed magnetic field and the software methods that allow to store the information storage device, but this today requires specialists to develop new ways of protecting information in order to avoid its leakage.

Influence of internal and external risks on sustainability of financial system of Аltai krai

2018 ◽  
Vol 35 (4) ◽  
pp. 133-136
Author(s):  
R. N. Ibragimov
Keyword(s):  
Sustainable Development ◽  
Financial Stability ◽  
Management Strategy ◽  
Financial System ◽  
Risk Management Strategy ◽  
The Sustainable Development ◽  
The Stability ◽  
The Impact

The article examines the impact of internal and external risks on the stability of the financial system of the Altai Territory. Classification of internal and external risks of decline, affecting the sustainable development of the financial system, is presented. A risk management strategy is proposed that will allow monitoring of risks, thereby these measures will help reduce the loss of financial stability and ensure the long-term development of the economy of the region.

scholarly journals In-Situ Annealed Ti3C2Tx MXene Based All-Solid-State Flexible Zn-Ion Hybrid Micro Supercapacitor Array with Enhanced Stability

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
La Li ◽  
Weijia Liu ◽  
Kai Jiang ◽  
Di Chen ◽  
Fengyu Qu ◽  
...  
Keyword(s):  
High Energy ◽  
High Rate ◽  
High Energy Density ◽  
Electrochemical Performances ◽  
Integrated Electronics ◽  
Long Term Stability ◽  
Hybrid Supercapacitors ◽  
Portable Electronics

AbstractZn-ion hybrid supercapacitors (SCs) are considered as promising energy storage owing to their high energy density compared to traditional SCs. How to realize the miniaturization, patterning, and flexibility of the Zn-ion SCs without affecting the electrochemical performances has special meanings for expanding their applications in wearable integrated electronics. Ti3C2Tx cathode with outstanding conductivity, unique lamellar structure and good mechanical flexibility has been demonstrated tremendous potential in the design of Zn-ion SCs, but achieving long cycling stability and high rate stability is still big challenges. Here, we proposed a facile laser writing approach to fabricate patterned Ti3C2Tx-based Zn-ion micro-supercapacitors (MSCs), followed by the in-situ anneal treatment of the assembled MSCs to improve the long-term stability, which exhibits 80% of the capacitance retention even after 50,000 charge/discharge cycles and superior rate stability. The influence of the cathode thickness on the electrochemical performance of the MSCs is also studied. When the thickness reaches 0.851 µm the maximum areal capacitance of 72.02 mF cm−2 at scan rate of 10 mV s−1, which is 1.77 times higher than that with a thickness of 0.329 µm (35.6 mF cm−2). Moreover, the fabricated Ti3C2Tx based Zn-ion MSCs have excellent flexibility, a digital timer can be driven by the single device even under bending state, a flexible LED displayer of “TiC” logo also can be easily lighted by the MSC arrays under twisting, crimping, and winding conditions, demonstrating the scalable fabrication and application of the fabricated MSCs in portable electronics.

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