Search Results - (( lesion classification technique ) OR ( evolution computing techniques ))

Stroke Lesion Segmentation And Classification For Diffusion-Weighted Imaging by Mohd Noor, Nor Shahirah

“…In conclusion, the proposed stroke classification technique has the potential to diagnose and classify brain stroke lesions.…”
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Brain Lesion Segmentation And Classification Using Diffusion-Weighted Imaging (DWI) by Muda, Ayuni Fateeha

“…Out of various MRI techniques, Diffusion-Weighted Imaging (DWI) remains the most accurate technique for early detection and discrimination of several brain lesions such as stroke. …”
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Multiclass classification for chest x-ray images based on lesion location in lung zones by Saad, Mohd Nizam, Muda, Zurina, Sahari, Noraidah, Abd Hamid, Hamzaini

“…Innovation in radiology technology has generated numerous kinds of medical images like the chest X-ray (CXR).This image is used to find common problem in lung like the lesion through scanning process in lung area which is divided into six zones.By classifying the CXR images with common feature like the lesion location, we can ensure efficient image retrieval.Recently, Support Vector Machine (SVM) has turn out to be a well-known method for image classification.While many previous studies have reported the achievement of SVM in classifying images, yet there is still problem with this technique for multiclass classification.Since SVM is a binary classification technique, its ability is limited to classifying features between two classes at one time. …”
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Automated Segmentation And Classification Technique For Brain Stroke by Mohd Saad, Norhashimah, Abdullah, Abdul Rahim, Mohd Noor, Niza Suzaini, Mohd Ali, Nursabillilah

“…This study proposes a segmentation and classification technique to detect brain stroke lesions based on diffusion-weighted imaging (DWI). …”
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Automatic Brain Lesion Detection And Classification Based On Diffusion-Weighted Imaging Using Adaptive Thresholding And A Rule-Based Classifier by Mohd Saad, Norhashimah, Abu-Bakar, Syed A.R., Muda, A.F., Muda, Sobri, Ahmad Radzi, Syafeeza

“…Overall,adaptive thresholding provides high segmentation performance for hyper-intensity lesions.The best segmentation and classification performance is achieved for acute stroke.The establishment of the technique could be used to automate the diagnosis and to clearly understand major brain lesions. …”
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Review Of Brain Lesion Detection And Classification Using Neuroimaging Analysis Techniques by Mohd Saad, Norhashimah, Abu Bakar, Syed Abdul Rahman Syed, Muda, Ahmad Sobri, Mokjib, Musa Mohd

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Automated diagnosis of focal liver lesions using bidirectional empirical mode decomposition features by Acharya, U. Rajendra, Koh, Joel En Wei, Hagiwara, Yuki, Tan, Jen Hong, Gertych, Arkadiusz, Vijayananthan, Anushya, Yaakup, Nur Adura, Abdullah, Basri Johan Jeet, Mohd Fabell, Mohd Kamil, Yeong, Chai Hong

“…The accuracy, sensitivity, and specificity of lesion classification were 92.95%, 90.80%, and 97.44%, respectively. …”
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Automated stroke lesion detection and diagnosis system by Mohd Saad, N., M. Noor, N. S., Abdullah, A. R., Muda, Ahmad Sobri, Muda, A. F., Abdul Rahman, N. N. S.

“…This study proposes a technique for automated detection and diagnosis of stroke lesions based on diffusion-weighted imaging (DWI). …”
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Automated detection of breast cancer in mammography images using Gabor filter and Bayesian classifier / Bardia Yousefi by Bardia, Yousefi

“…The objective of this research is developing a technique for feature extraction in breast lesions by applying Gabor filter and using Bayesian classifier for classification of the breast lesions. …”
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Novel techniques for enhancement and segmentation of acne vulgaris lesions by Malik, A. S., Humayun, J., Kamel, N., Yap, F. B.-B.

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Development of Hybrid Convolutional Neural Network and Auto-Regressive Integrated Moving Average for Skin Cancer Classification by KA CHIN, CHEE

“…The suitable image pre-processing technique and image augmentation method are identified to avoid the degradation of classification accuracy in this research. …”
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A Novel Algorithm for Breast Lesion Detection Using Textons and Local Configuration Pattern Features With Ultrasound Imagery by Acharya, U. Rajendra, Meiburger, Kristen M., Wei Koh, Joel En, Ciaccio, Edward J., Arunkumar, N., See, Mee Hoong, Mohd Taib, Nur Aishah, Vijayananthan, Anushya, Rahmat, Kartini, Fadzli, Farhana, Leong, Sook Sam, Westerhout, Caroline Judy, Chantre-Astaiza, Angela, Ramirez-Gonzalez, Gustavo

“…This paper presents a novel method for the detection of breast lesions in ultrasound images using texton filter banks, local configuration pattern features, and classification, without employing any segmentation technique. …”
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Thyroid lesion classification in 242 patient population using Gabor transform features from high resolution ultrasound images by Acharya, U.R., Chowriappa, P., Fujita, H., Bhat, S., Dua, S., Koh, J.E.W., Eugene, L.W.J., Kongmebhol, P., Ng, K.H.

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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

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Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization by Yahya, Zainor Ridzuan

“…For each proposed soft computing technique, parameter tuning is done as an essential study. …”
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Application Of Artificial Neural Networks in the Classification of Cervical Cells Based on the Bethesda System by Mat Isa, Nor Ashidi, Mashor, Mohd Yusoff, Othman, Nor Hayati, Zamli, Kamal Zuhairi

“…In the second stage, we classify cervical cells abnormality into three classes based on The Bethesda Classification System; normal, low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL). …”
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Computer-aided screening system for cervical precancerous cells based on field emission scanning electron microscopy and energy dispersive x-ray / Yessi Jusman by Yessi, Jusman

“…Finally, for the classification stage, the Discriminant Analysis (DA) concept was used to classify the cervical precancerous cells based on the Bethesda system (i.e. normal, Low-grade Squamous Intraepithelial Lesion (LSIL) and High-grade Squamous Intraepithelial Lesion (HSIL)). …”
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Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images by Mohd Saad, Norhashimah, Azman, Izzatul Husna, Abdullah, Abdul Rahim, Hamzah, Rostam Affendi, Muda, Ahmad Sobri, Yamba, Farzanah Atikah

“…A hybrid segmentation technique, fuzzy c-means with active contour (FCMAC), is proposed to enhance lesion localization accuracy. …”
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Detection of lesion of lung cancer in CT scan images using watershed segmentation / Nur Najihah Sofia Mohd Marzuki …[et al.] by Mohd Marzuki, Nur Najihah Sofia, Sulaiman, Siti Noraini, Isa, Iza Sazanita, A.Karim, Noor Khairiah, Md Tahir, Nooritawati

“…The lung lobes and nodules or lesion in CT image are segmented using two techniques which are convolution watershed and modified watershed within two stage approaches. …”
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Effect of color feature normalization on segmentation of color images by Khan, J., Malik, A.S., Kamel, N., Das, S.C., Affandi, A.M.

“…In this paper, an unsupervised technique is proposed for the segmentation of acne vulgaris lesions. …”
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