Segmentasi Citra Mri Menggunakan Deteksi Tepi Untuk Identifikasi Kanker Payudara

2017 ◽  
Vol 15 (2) ◽  
pp. 17 ◽  
Author(s):  
Ervina Varijki ◽  
Bambang Krismono Triwijoyo
Keyword(s):  
Breast Cancer ◽  
Edge Detection ◽  
Object Segmentation ◽  
Computation Time ◽  
Input Image ◽  
Boundary Line ◽  
Cancer Breast ◽  
Average Computation Time ◽  
Breast Cancer Mri ◽  
Image Format

One type of cancer that is capable identified using MRI technology is breast cancer. Breast cancer is still the leading cause of death world. therefore early detection of this disease is needed. In identifying breast cancer, a doctor or radiologist analyzing the results of magnetic resonance image that is stored in the format of the Digital Imaging Communication In Medicine (DICOM). It takes skill and experience sufficient for diagnosis is appropriate, andaccurate, so it is necessary to create a digital image processing applications by utilizing the process of object segmentation and edge detection to assist the physician or radiologist in identifying breast cancer. MRI image segmentation using edge detection to identification of breast cancer using a method stages gryascale change the image format, then the binary image thresholding and edge detection process using the latest Robert operator. Of the20 tested the input image to produce images with the appearance of the boundary line of each region or object that is visible and there are no edges are cut off, with the average computation time less than one minute.

Gaussian and Gabor Filter Approach for Object Segmentation

2014 ◽  
Vol 14 (2) ◽  
Author(s):  
S. Thilagamani ◽  
N. Shanthi
Keyword(s):  
Edge Detection ◽  
Object Segmentation ◽  
Gabor Filter ◽  
Region Growing ◽  
Input Image ◽  
Bilateral Filtering ◽  
Efficient Approach ◽  
Filter Approach ◽  
The Given

The problem of segmenting the object from the background is addressed in the proposed Gaussian and Gabor Filter Approach (GGFA) for object segmentation. An improved and efficient approach based on Gaussian and Gabor Filter reads the given input image and performs filtering and smoothing operation. The region occupied by the object is extracted from the image by performing various operations like bilateral filtering, Edge detection, Clustering, and Region growing. The proposed approach experimented on standard images taken from Caltech datasets, Corel Photo CDs, and Weizmann horse datasets show significantly improved results.

scholarly journals Implementation of Sobel Method Based Edge Detection for Flower Image Segmentation

SinkrOn ◽  
2019 ◽  
Vol 3 (2) ◽  
pp. 161
Author(s):  
Asmaidi Asmaidi ◽  
Darma Setiawan Putra ◽  
Muharratul Mina Risky ◽  
Fitria Ulfa R
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Programming Language ◽  
Image Data ◽  
Input Image ◽  
Interactive System ◽  
Boundary Line ◽  
Pixel Value

Edge detection is the first step to cover information in the image. The edges characterize the boundaries of objects and therefore edges are useful for the process of segmentation and identification in the image. The purpose of edge detection is to increase the appearance of the boundary line of the object in the image. The sobel method is a method that uses two kernels measuring 3x3 pixels for gradient calculations so that the estimate gradient is right in the middle of the window. Digital image processing aims to manipulate image data and analyze an image with the help of a computer. Matlab is made to facilitate the use of two collections of subroutines in the fortran library, linpack and eispack, in handling matrix computing, and develops into an interactive system as a programming language. Experimental results from the input image research, namely the flower image have different MSE values because each input image has a different pixel value

THE PREVALENCE OF HEPATITIS B REACTIVATION (HBV) IN CANCER PATIENTS TREATING WITH CHEMOTHERAPY

2016 ◽  
pp. 74-80
Author(s):  
Phuong Phung ◽  
Thi Thuy Nguyen
Keyword(s):  
Breast Cancer ◽  
Lung Cancer ◽  
Hepatitis B ◽  
Cancer Patients ◽  
Positive Control ◽  
High Dose ◽  
Hbv Reactivation ◽  
Endemic Region ◽  
Hepatitis B Reactivation ◽  
Cancer Breast

ackground and Objectives: Nowadays, the incidence of cancer is constantly increasing in the world as well as in Vietnam. The treatment of cancer is based on multimodality principle. Among those principal modalities, chemotherapy is widely used for different purposes such as neoadjuvant, andjuvant and palliation. However, chemotherapy can induce activation of latent infections, including hepatitis B. Vietnam is in the endemic region of hepatitis B so the reactivation of hepatitis B on cancer patients with chemotherapy has emerged a concerned problem. However, few interests were gained on this problem in the aspect of clinical setting or researching. Aims: to determine the prevalence of hepatitis B reactivation (HBV) in cancer patients treating with chemotherapy and to detect some risks factors of this situation. Subjects and methods: descriptive prospective. The study included 33 cancer patients with inactive HBV infection who are treating with chemotherapy. We define HBV reactivation by ALT > 3 ULN and HBV DNA copies > 10 positive control limit. Results: We found 6 patients with reactivated HBV, accounting for 18.18 %. Among reactivated HBV patients, age less than 60 accounts 83,33%. Rate of reactivated HBV in males was 25,00% while this rate in females was 14,28%. Rate of reactivated HBV in lymphoma, lung cancer and breast cancer was 33,33%, 25% và 22,22% respectively. Clinial manifestation of reactivated HBV includes jaundice (33,33%), fulminant hepatic failure (6%) and death (5%). The reactivated rate was higher in patients got high dose of corticoid (28,57%) vs low dose (15,38%). This rate was 29,41% in patients treated with anthracyclines which was higher than in group without anthracyclines. The reactivated rate of HBV was dramatically higher in patients treated with rituximab (75%). Conclusion: the reactivation of hepatitis B on cancer patients with chemotherapy is common. We found 6 patients with reactivated HBV of 33 subjects of the study which accounts 18.18 %. We recognized that reactivated HBV rate was higher subgroups of age < 60 years old, males, patients with lymphoma, lung cancer, breast cancer. Reactivated HBV may be more prevalent in patients with high-dose corticotherapy, anthracyclines and Rituximab. Key words: HBV reactivation, chemotherapy, cancer, hepatitis B

Determinan Kejadian Ca Mammae Di Poli Rawat Jalan Bedah Rsud Dr. Achmad Mochtar

2018 ◽  
Vol 3 (3) ◽  
pp. 575
Author(s):  
Neila Sulung ◽  
Rizki Yananda ◽  
Adriani Adriani
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Incidence ◽  
Hormonal Contraception ◽  
Sampling Technique ◽  
Case Control ◽  
Female Breast Cancer ◽  
Chi Square ◽  
Control Approach ◽  
Factors Associated ◽  
Cancer Breast

<p>Cancer is one of the leading causes of death worldwide. In Indonesia every year 1: 3 women per 1000 population are affected by breast cancer. Breast cancer is a cancer that attacks most women. The incidence of breast cancer is currently estimated at 39 per 100,000 population in 2008. The purpose of this study was to determine the factors associated with the risk of female breast cancer in surgical outpatient poly patients at Dr. Achmad Mochtar, Bukittinggi City. This study uses descriptive analytic method with a case control approach. The sampling technique in this study was accidental sampling. The sample in this study were all women diagnosed with breast cancer, amounting to 50 cases and 50 controls with data processing through computerization. The instrument used in this study is a questionnaire. Data analysis was performed using Chi-Square test (α = 0.05). The results showed that the factors associated with the incidence of breast cancer were genetic (p = 0.009), menarche (p = 0.014), menopause (p = 0.016), hormonal contraception (p = 0,045), obesity (p = 0,043), and high food fat (p = 0.028).  Conclusions of the study are factors related to the risk of breast cancer incidence are genetic, menarche, menopause, hormonal contraception, obesity and high-fat foods.<br /> </p><p>Penyakit kanker merupakan salah satu penyebab kematian utama di seluruh dunia. Di Indonesia setiap tahun 1:3 wanita per 1000 penduduk terserang kanker payudara. Kanker payudara merupakan kanker yang paling banyak menyerang perempuan. Angka kejadian kanker payudara saat ini diperkirakan 39 per 100.000 penduduk pada tahun 2008. Tujuan penelitian ini adalah untuk mengetahui faktor-faktor yang berhubungan dengan risiko kanker payudara wanita pada pasien poli rawat jalan bedah di RSUD Dr. Achmad Mochtar Kota Bukittinggi. Penelitian ini menggunakan metode <em>deskriptif analitik</em> dengan pendekatan <em>case control</em>. Teknik pengambilan sampel dalam penelitian ini adalah <em>accidental sampling.</em> Sampel dalam penelitian ini adalah semua wanita yang terdiagnosis kanker payudara, berjumlah 50 kasus dan 50 kontrol dengan pengolahan data melalui komputerisasi. Instrument yang digunakan dalam penelitian ini adalah lembar kuisioner. Analisis data dilakukan menggunakan uji <em>Chi-Square </em>(α=0,05). Hasil penelitian menunjukkan faktor yang berhubungan dengan kejadian kanker payudara adalah genetik (p=0,009), <em>menarche</em> (p=0,014;), <em>menopause</em> (p=0,016), kontrasepsi hormonal (p=0,045), <em>obesitas </em>(p=0,043), dan makanan tinggi lemak (p=0,028). Simpulan penelitian adalah faktor yang berhubungan dengan risiko kejadian kanker payudara adalah genetik, <em>menarche, menopause,</em> kontrasepsi hormonal, <em>obesitas</em> dan makanan tinggi lemak.</p>

A STRUCTURAL APPROACH TO ON-LINE CHARACTER RECOGNITION: SYSTEM DESIGN AND APPLICATIONS

1991 ◽  
Vol 05 (01n02) ◽  
pp. 311-335 ◽  
Author(s):  
FATHALLAH NOUBOUD ◽  
RÉJEAN PLAMONDON
Keyword(s):  
Character Recognition ◽  
Computation Time ◽  
Experimental Tests ◽  
Recognition System ◽  
Structural Approach ◽  
Chain Code ◽  
String Comparison ◽  
Average Computation Time ◽  
On Line ◽  
A Chain

This paper presents a real-time constraint-free handprinted character recognition system based on a structural approach. After the preprocessing operation, a chain code is extracted to represent the character. The classification is based on the use of a processor dedicated to string comparison. The average computation time to recognize a character is about 0.07 seconds. During the learning step, the user can define any set of characters or symbols to be recognized by the system. Thus there are no constraints on the handprinting. The experimental tests show a high degree of accuracy (96%) for writer-dependent applications. Comparisons with other system and methods are discussed. We also present a comparison between the processor used in this system and the Wagner and Fischer algorithm. Finally, we describe some applications of the system.

Computer-assisted Diagnosis for Early Stage Pleural Mesothelioma

2007 ◽  
Vol 46 (03) ◽  
pp. 324-331 ◽  
Author(s):  
P. Jäger ◽  
S. Vogel ◽  
A. Knepper ◽  
T. Kraus ◽  
T. Aach ◽  
...  
Keyword(s):  
Early Stage ◽  
Computation Time ◽  
Hounsfield Unit ◽  
Computer Assisted ◽  
Clinical Test ◽  
Pleural Mesothelioma ◽  
Data Sets ◽  
Data Set ◽  
Average Computation Time ◽  
Ct Data

Summary Objectives: Pleural thickenings as biomarker of exposure to asbestos may evolve into malignant pleural mesothelioma. Foritsearly stage, pleurectomy with perioperative treatment can reduce morbidity and mortality. The diagnosis is based on a visual investigation of CT images, which is a time-consuming and subjective procedure. Our aim is to develop an automatic image processing approach to detect and quantitatively assess pleural thickenings. Methods: We first segment the lung areas, and identify the pleural contours. A convexity model is then used together with a Hounsfield unit threshold to detect pleural thickenings. The assessment of the detected pleural thickenings is based on a spline-based model of the healthy pleura. Results: Tests were carried out on 14 data sets from three patients. In all cases, pleural contours were reliably identified, and pleural thickenings detected. PC-based Computation times were 85 min for a data set of 716 slices, 35 min for 401 slices, and 4 min for 75 slices, resulting in an average computation time of about 5.2 s per slice. Visualizations of pleurae and detected thickeningswere provided. Conclusion: Results obtained so far indicate that our approach is able to assist physicians in the tedious task of finding and quantifying pleural thickenings in CT data. In the next step, our system will undergo an evaluation in a clinical test setting using routine CT data to quantifyits performance.

scholarly journals Improving ozone profile retrieval from spaceborne UV backscatter spectrometers using convergence behaviour diagnostics

2010 ◽  
Vol 3 (6) ◽  
pp. 1555-1568 ◽  
Author(s):  
B. Mijling ◽  
O. N. E. Tuinder ◽  
R. F. van Oss ◽  
R. J. van der A
Keyword(s):  
Cross Sections ◽  
A Priori ◽  
Computation Time ◽  
External Input ◽  
Computational Time ◽  
Ozone Profile ◽  
Global Performance ◽  
Convergence Behaviour ◽  
Low Cloud ◽  
Average Computation Time

Abstract. The Ozone Profile Algorithm (OPERA), developed at KNMI, retrieves the vertical ozone distribution from nadir spectral satellite measurements of back scattered sunlight in the ultraviolet and visible wavelength range. To produce consistent global datasets the algorithm needs to have good global performance, while short computation time facilitates the use of the algorithm in near real time applications. To test the global performance of the algorithm we look at the convergence behaviour as diagnostic tool of the ozone profile retrievals from the GOME instrument (on board ERS-2) for February and October 1998. In this way, we uncover different classes of retrieval problems, related to the South Atlantic Anomaly, low cloud fractions over deserts, desert dust outflow over the ocean, and the intertropical convergence zone. The influence of the first guess and the external input data including the ozone cross-sections and the ozone climatologies on the retrieval performance is also investigated. By using a priori ozone profiles which are selected on the expected total ozone column, retrieval problems due to anomalous ozone distributions (such as in the ozone hole) can be avoided. By applying the algorithm adaptations the convergence statistics improve considerably, not only increasing the number of successful retrievals, but also reducing the average computation time, due to less iteration steps per retrieval. For February 1998, non-convergence was brought down from 10.7% to 2.1%, while the mean number of iteration steps (which dominates the computational time) dropped 26% from 5.11 to 3.79.

scholarly journals Ideal Huffman Code for Lossless Image Compression for Ubiquitous Access

2018 ◽  
Vol 12 (2) ◽  
pp. 765 ◽  
Author(s):  
T Kavitha ◽  
K. Jayasankar
Keyword(s):  
Image Compression ◽  
Smart Phone ◽  
Computation Time ◽  
Digital Data ◽  
Compression Technique ◽  
Lossless Image Compression ◽  
Coding Efficiency ◽  
Average Computation Time ◽  
Ubiquitous Access ◽  
Cloud Storage Environment

<p>Compression technique is adopted to solve various big data problems such as storage and transmission. The growth of cloud computing and smart phone industries has led to generation of huge volume of digital data. Digital data can be in various forms as audio, video, images and documents. These digital data are generally compressed and stored in cloud storage environment. Efficient storing and retrieval mechanism of digital data by adopting good compression technique will result in reducing cost. The compression technique is composed of lossy and lossless compression technique. Here we consider Lossless image compression technique, minimizing the number of bits for encoding will aid in improving the coding efficiency and high compression. Fixed length coding cannot assure in minimizing bit length. In order to minimize the bits variable Length codes with prefix-free codes nature are preferred. However the existing compression model presented induce high computing overhead, to address this issue, this work presents an ideal and efficient modified Huffman technique that improves compression factor up to 33.44% for Bi-level images and 32.578% for Half-tone Images. The average computation time both encoding and decoding shows an improvement of 20.73% for Bi-level images and 28.71% for Half-tone images. The proposed work has achieved overall 2% increase in coding efficiency, reduced memory usage of 0.435% for Bi-level images and 0.19% for Half-tone Images. The overall result achieved shows that the proposed model can be adopted to support ubiquitous access to digital data.</p>

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