Comput Methods Programs Biomed - Robust information gain based fuzzy c-means clustering and classification of carotid artery ultrasound images.

Tópicos

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Resumo

In this paper, a robust method is proposed for segmentation of medical images by exploiting the concept of information gain. Medical images contain inherent noise due to imaging equipment, operating environment and patient movement during image acquisition. A robust medical image segmentation technique is thus inevitable for accurate results in subsequent stages. The clustering technique proposed in this work updates fuzzy membership values and cluster centroids based on information gain computed from the local neighborhood of a pixel. The proposed approach is less sensitive to noise and produces homogeneous clustering. Experiments are performed on medical and non-medical images and results are compared with state of the art segmentation approaches. Analysis of visual and quantitative results verifies that the proposed approach outperforms other techniques both on noisy and noise free images. Furthermore, the proposed technique is used to segment a dataset of 300 real carotid artery ultrasound images. A decision system for plaque detection in the carotid artery is then proposed. Intima media thickness (IMT) is measured from the segmented images produced by the proposed approach. A feature vector based on IMT values is constructed for making decision about the presence of plaque in carotid artery using probabilistic neural network (PNN). The proposed decision system detects plaque in carotid artery images with high accuracy. Finally, effect of the proposed segmentation technique has also been investigated on classification of carotid artery ultrasound images.

Resumo Limpo

paper robust method propos segment medic imag exploit concept inform gain medic imag contain inher nois due imag equip oper environ patient movement imag acquisit robust medic imag segment techniqu thus inevit accur result subsequ stage cluster techniqu propos work updat fuzzi membership valu cluster centroid base inform gain comput local neighborhood pixel propos approach less sensit nois produc homogen cluster experi perform medic nonmed imag result compar state art segment approach analysi visual quantit result verifi propos approach outperform techniqu noisi nois free imag furthermor propos techniqu use segment dataset real carotid arteri ultrasound imag decis system plaqu detect carotid arteri propos intima media thick imt measur segment imag produc propos approach featur vector base imt valu construct make decis presenc plaqu carotid arteri use probabilist neural network pnn propos decis system detect plaqu carotid arteri imag high accuraci final effect propos segment techniqu also investig classif carotid arteri ultrasound imag

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