scholarly journals Segmentation and Labelling of Human Spine MR Images Using Fuzzy Clustering

2016 ◽  
Author(s):  
Jiyo S.Athertya ◽  
Saravana Kumar G
Keyword(s):  
Fuzzy Clustering ◽  
Mr Images ◽  
Human Spine ◽  
Spine Mr

scholarly journals DC2Anet: Generating Lumbar Spine MR Images from CT Scan Data Based on Semi-Supervised Learning

2019 ◽  
Vol 9 (12) ◽  
pp. 2521 ◽  
Author(s):  
Cheng-Bin Jin ◽  
Hakil Kim ◽  
Mingjie Liu ◽  
In Ho Han ◽  
Jae Il Lee ◽  
...  
Keyword(s):  
Lumbar Spine ◽  
Objective Function ◽  
Supervised Learning ◽  
Lumbar Disc ◽  
Mr Images ◽  
Disc Disease ◽  
Cardiac Pacemakers ◽  
Lumbar Disc Disease ◽  
Adversarial Network ◽  
Spine Mr

Magnetic resonance imaging (MRI) plays a significant role in the diagnosis of lumbar disc disease. However, the use of MRI is limited because of its high cost and significant operating and processing time. More importantly, MRI is contraindicated for some patients with claustrophobia or cardiac pacemakers due to the possibility of injury. In contrast, computed tomography (CT) scans are much less expensive, are faster, and do not face the same limitations. In this paper, we propose a method for estimating lumbar spine MR images based on CT images using a novel objective function and a dual cycle-consistent adversarial network (DC 2 Anet) with semi-supervised learning. The objective function includes six independent loss terms to balance quantitative and qualitative losses, enabling the generation of a realistic and accurate synthetic MR image. DC 2 Anet is also capable of semi-supervised learning, and the network is general enough for supervised or unsupervised setups. Experimental results prove that the method is accurate, being able to construct MR images that closely approximate reference MR images, while also outperforming four other state-of-the-art methods.

ENHANCEMENT TECHNIQUES FOR MRI HUMAN SPINE IMAGES

2015 ◽  
Vol 77 (6) ◽  
Author(s):  
Aqilah Baseri Huddin ◽  
W Mimi Diyana W Zaki ◽  
Agnes Chung Wai Mun ◽  
Ling Chei Siong ◽  
Hamzaini Abdul Hamid
Keyword(s):  
Magnetic Resonance Image ◽  
Discrete Wavelet ◽  
Mr Images ◽  
Image Preprocessing ◽  
Image Processing Techniques ◽  
Human Spine ◽  
Human Soft Tissue ◽  
Herniated Disk ◽  
Processing Techniques

The quality of Magnetic Resonance Image (MRI) determines the accuracy of clinical diagnosis. It provides information about the human soft tissue anatomy. MRI of spine is used by the physicians to evaluate any presence of diseases including slipped disk, herniated disk, trauma and disk degeneration. Existence of noises and artifacts can degrade the quality of the MR images. Thus, appropriate image processing techniques may help to improve the quality of the acquired image. Preprocessing is usually done to remove the noise, enhance an image boundary and adjust the image contrast. Current techniques to enhance and reduce noise in MRI human spine are discussed and a method using discrete wavelet transform to enhance the MRI of human spine is proposed. The resultant images are evaluated quantitatively. This study shows that the proposed method has better results as compared to other existing method based on evaluation tests. 

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