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Machine learning-based novel approach to classify the shoulder motion of upper limb amputees
Publication date: Available online 8 August 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Kaur AmanpreetAbstractAn upper limb amputation is a traumatic event that can seriously affect the person’s capacity to perform regular tasks and can lead individuals to lose their confidence and autonomy. Prosthetic devices can be controlled via the acquisition and processing of electromyogram signal produced at the muscles fiber from the surface of the body with an array of an electrode placed on the residual limb. This paper presents the feasibility of classifying the different shoulder movements from around shou...
Source: Biocybernetics and Biomedical Engineering - August 9, 2019 Category: Biomedical Engineering Source Type: research

Social-group-optimization based tumor evaluation tool for clinical brain MRI of flair/DW modality
This article proposes a two-stage image assessment tool to examine brain MR images acquired using the Flair and DW modalities. The combination of the Social-Group-Optimization (SGO) and Shannon's-Entropy (SE) supported multi-thresholding is implemented to pre-processing the input images. The image post-processing includes several procedures, such as Active Contour (AC), Watershed and region-growing segmentation, to extract the tumor section. Finally, a classifier system is implemented using ANFIS to categorize the tumor under analysis into benign and malignant. Experimental investigation was executed using benchmark datase...
Source: Biocybernetics and Biomedical Engineering - July 27, 2019 Category: Biomedical Engineering Source Type: research

Single channel EMG-based continuous terrain identification with simple classifier for lower limb prosthesis
Publication date: Available online 20 July 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Rohit Gupta, Ravinder AgarwalAbstractThe focus of the present research endeavour is to propose a single channel electromyogram (EMG) signal driven continuous terrain identification method utilizing a simple classifier. An iterative feature selection algorithm has also been proposed to provide effective information to the classifiers. The proposed method has been validated on EMG signal of fifteen subjects (ten men, five women) for three daily life terrains. Feature selection algorithm has significantly improved the id...
Source: Biocybernetics and Biomedical Engineering - July 21, 2019 Category: Biomedical Engineering Source Type: research

In vitro and in vivo evaluation of novel Tadalafil/β-TCP/Collagen scaffold for bone regeneration: A rabbit critical-size calvarial defect study
This study highlights the promising application of TβC scaffold with Tadalafil for successful bone regeneration by enhancing osteogenesis. (Source: Biocybernetics and Biomedical Engineering)
Source: Biocybernetics and Biomedical Engineering - July 21, 2019 Category: Biomedical Engineering Source Type: research

Machine learning methods for MRI biomarkers analysis of pediatric posterior fossa tumors
We present a machine learning based magnetic resonance imaging biomarkers analysis framework for two kinds of pediatric posterior fossa tumors. In details, three feature extraction methods are used to obtain 300 imaging biomarkers. 10 feature selection methods and 11 classifiers are evaluated by the quantified predictive performance and stability, and importance consistency of features and the influence of the experimental factors are also analyzed. Our results demonstrate that the CFS feature selection method (accuracy: 83.85 ± 5.51%, stability: [0.84, 0.06]) and SVM classifier (accuracy: 85.38 ± 3.4...
Source: Biocybernetics and Biomedical Engineering - July 21, 2019 Category: Biomedical Engineering Source Type: research

A hybrid method for blood vessel segmentation in images
Publication date: Available online 21 July 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Díaz Primitivo, Rodríguez Alma, Cuevas Erik, Valdivia Arturo, Chavolla Edgar, Pérez-Cisneros Marco, Zaldívar DanielAbstractIn the last years, image processing has been an important tool for health care. The analysis of retinal vessel images has become crucial to achieving a better diagnosis and treatment for several cardiovascular and ophthalmological deceases. Therefore, an automatic and accurate procedure for retinal vessel and optic disc segmentation is essential for illness detection. This task is extremely ha...
Source: Biocybernetics and Biomedical Engineering - July 21, 2019 Category: Biomedical Engineering Source Type: research

Robust intensity variation and inverse surface adaptive thresholding techniques for detection of optic disc and exudates in retinal fundus images
Publication date: Available online 9 July 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): S. Karkuzhali, D. ManimegalaiAbstractDiabetic Retinopathy (DR) is an adverse change in retinal blood vessels leads to blindness for diabetic patients without any symptoms. Diabetes is characterized by imbalance level of glucose in the human body. The optic disc (OD) is the major retinal landmark. Localization of OD is an important step in fundus image analysis and to develop Computer Aided Diagnosis tool for DR. OD center detection is necessary to reduce false positive rate in the detection of exudates (EXs). EXs is th...
Source: Biocybernetics and Biomedical Engineering - July 11, 2019 Category: Biomedical Engineering Source Type: research

Plantar pressure image fusion for comfort fusion in diabetes mellitus using an improved fuzzy hidden Markov model
Publication date: Available online 1 July 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Zairan Li, Dan Wang, Nilanjan Dey, Amira S. Ashour, R. Simon Sherratt, Fuqian ShiAbstractDiabetes mellitus is a clinical syndrome caused by the interaction of genetic and environmental factors. The change of plantar pressure in diabetic patients is one of the important reasons for the occurrence of diabetic foot. The abnormal increase of plantar pressure is a predictor of the common occurrence of foot ulcers. The feature extraction of plantar pressure distribution will be beneficial to the design and manufacture of dia...
Source: Biocybernetics and Biomedical Engineering - July 2, 2019 Category: Biomedical Engineering Source Type: research

Kernel-based Fisher discriminant analysis on the Riemannian manifold for nuclear atypia scoring of breast cancer
Publication date: Available online 30 June 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Asha Das, Madhu S. Nair, S. David PeterAbstractBreast carcinoma is the most prevalent type of malignancy among women worldwide. Breast cancer grading often termed as Nuclear Atypia Scoring (NAS) forms a significant factor in determining individualized treatment plans and in the prognosis of the disease. For addressing the problem of breast cancer grading, we attempt to model the variations in features between histopathological images of different cancer grades and thereby explore the discriminative information conceal...
Source: Biocybernetics and Biomedical Engineering - June 30, 2019 Category: Biomedical Engineering Source Type: research

Automated characterization and classification of coronary atherosclerotic plaques for intravascular optical coherence tomography
This study aimed to propose a novel plaque characterization algorithm to automatically characterize and classify the atherosclerotic plaques (fibrous, calcific, and lipid-rich). First, nongeometric features such as Fisher vector, principal component analysis, histogram of the oriented gradient, and local binary pattern were investigated and adapted to two geometric features (basic feature and texture feature) to characterize the plaques. Second, for automated classification of the plaques, a hard example mining strategy was introduced to train support vector machine classifier and improve the effectiveness of training data...
Source: Biocybernetics and Biomedical Engineering - June 26, 2019 Category: Biomedical Engineering Source Type: research

Selecting the optimal conditions of Savitzky–Golay filter for fNIRS signal
Publication date: Available online 14 June 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Md. Asadur Rahman, Mohd Abdur Rashid, Mohiuddin AhmadAbstractThis paper proposes a method to find the best conditions for applying Savitzky–Golay (SG) filter to remove physiological noises from the functional near-infrared spectroscopy (fNIRS) signal. A narrative review on existing physiological noise reduction techniques from fNIRS signal demonstrates that the most common methods are window based finite impulse response (FIR) and SG filters. However, these filters did not clarify why and how it is able to remove no...
Source: Biocybernetics and Biomedical Engineering - June 14, 2019 Category: Biomedical Engineering Source Type: research

Cerebral edema segmentation using textural feature
Publication date: Available online 11 June 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Archana Chaudhari, Jayant KulkarniAbstractDiagnostic imaging provides a vital tool in detection and analysis of Brain pathologies. Magnetic resonance imaging (MRI) provides an effective means for non-invasive mapping of anatomy and pathology in the brain. Pathologies like cerebral edema and tumors can spread in different tissues in the brain and can affect cognitive and other functions in the body. Accurate segmentation is therefore a challenging task. Human Brain consists of different soft tissues. These tissues can ...
Source: Biocybernetics and Biomedical Engineering - June 12, 2019 Category: Biomedical Engineering Source Type: research

A deep learning model integrating SK-TPCNN and random forests for brain tumor segmentation in MRI
Publication date: Available online 12 June 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Tiejun Yang, Jikun Song, Lei LiAbstractThe segmentation of brain tumors in magnetic resonance imaging (MRI) images plays an important role in early diagnosis, treatment planning and outcome evaluation. However, due to gliomas’ significant diversity in structure, the segmentation accuracy is low. In this paper, an automatic segmentation method integrating the small kernels two-path convolutional neural network (SK-TPCNN) and random forests (RF) is proposed, the feature extraction ability of SK-TPCNN and the joint opt...
Source: Biocybernetics and Biomedical Engineering - June 12, 2019 Category: Biomedical Engineering Source Type: research

Two stage contour evolution for automatic segmentation of choroid and cornea in OCT images
Publication date: Available online 5 June 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Neetha George, C.V. JijiAbstractEnhanced depth imaging optical coherence tomography (EDI OCT) enables visualization of deeper layers of retina, the segmentation of which can help in the diagnosis of many ophthalmic diseases. Though, a wide variety of segmentation algorithms are available for clinical practice in retinal analysis, segmentation of cornea and choroid are still done manually due to the lack of automated segmentation tools. This paper proposes a multilevel contour evolution approach for segmenting various l...
Source: Biocybernetics and Biomedical Engineering - June 6, 2019 Category: Biomedical Engineering Source Type: research

Decision tree for modeling survival data with competing risks
Publication date: Available online 4 June 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Kazeem Adesina Dauda, Biswabrata Pradhan, B. Uma Shankar, Sushmita MitraAbstractThis work considers decision tree for modeling survival data with competing risks. A Survival Classification and Regression Tree (SCART) technique is proposed for analysing survival data by modifying classification and regression tree (CART) algorithm to handle censored data for both regression and classification problems. Different performance measures for regression and classification tree are proposed. Model validation is done by two dif...
Source: Biocybernetics and Biomedical Engineering - June 5, 2019 Category: Biomedical Engineering Source Type: research