Morphometry of the Uncinate Process, Vertebral Body, and Lamina of the C3–7 Vertebrae Relevant to Cervical Spine Surgery

Veeramani Raveendranath,Thangarasu Kavitha,Amirthalingam Umamageswari 대한척추신경외과학회 2019 Neurospine Vol.16 No.4

Objective: The cervical spine consists of 4 typical and 3 atypical vertebrae. The uncinate process is one of the unique features of the cervical vertebrae. Uncinectomy and uncoforaminotomy are widely used to decompress the nerve in the intervertebral foramen and to remove osteophytes from the uncinate process. Morphometric analyses of the uncinate process help spine surgeons obtain a 3-dimensional orientation for approaching the cervical spine with minimal risk to the surrounding vascular and neural structures. This study aims to analyze the morphometry of uncinate process of cervical vertebrae with relevant to cervical spine surgery. Methods: Eighty dry adult cervical vertebrae were studied, and 11 parameters were measured. Seven parameters were paired and 4 were unpaired. Results: The height of the uncinate process progressively increased from C3 to C6 and decreased at C7. The length of the uncinate process increased from C3 to C6–7. The width was greatest at C6 and smallest at C3. The vertebral body width and anteroposterior diameter gradually increased from C3 to C7. The parameters of the lamina also increased from C3 to C7. Conclusion: Precise knowledge about the cervical vertebrae is useful for diagnosing both common and uncommon causes of symptoms and for choosing an appropriate approach. Thus, it helps to increase the success rate of cervical surgery.

Land Registration: Use-case of e-Governance using Blockchain Technology

( Karthika Veeramani ),( Suresh Jaganathan ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.9

e-Governance is a medium to offer various services to citizens through a web portal, that exists in many countries nowadays. The existing e-Governance technology is a vast, centrally managed database and a set of applications that connect to it via web interfaces. Despite the modernisation of services, it remains with the lack of transparency. Thus, the existing infrastructure of e-Governance paves the way for corrupt practises by the bureaucrats. e-Governance needs a powerful underlying technology which doesn't provide any way to allow tampering of the record and which in turn eliminates corruption. In this paper, we took land registration as a use-case for building e-Governance by keeping Blockchain as an underlying technology, to put off the corrupt practices and to bring transparency. Once transactions in land registration added to the Blockchain, it is immutable as it is cryptographically secured. Besides, the blockchain technology is secured as the ledger is distributed over the network. If a hacker wants to modify the ledger, he needs to hack every node in the blockchain network. Hyperledger Fabric, a permissioned Blockchain adopted for implementation and Hyperledger Caliper for performance analysis with these evaluation metrics such as throughput, latency and execution time.

Morphometric study of tensor of vastus intermedius in South Indian population

Raveendranath Veeramani,Dhivyalakshmi Gnanasekaran 대한해부학회 2017 Anatomy & Cell Biology Vol.50 No.1

Tensor of vastus intermedius is a newly discovered muscle located between vastus lateralis and vastus intermedius. The purpose of this study was to investigate the detailed morphology of tensor of vastus intermedius, specifically to provide data pertaining to the attachments, innervations, variation in the types and its morphometry in South Indian population. The tensor of vastus intermedius was studied in thirty six cadaveric lower limbs using macrodissection techniques. The origin of the muscle was from upper part of intertrochanteric line and anterior part of greater trochanter of femur inserted to medial aspect of upper border of patella. The muscle was classified into four types based on the origin and also the aponeurosis course with independent type (type 1) being common. The mean and standard deviation of the length of tensor of vastus intermedius and aponeurosis were 145.40±37.55 mm and 193.55±42.32 mm, respectively. The results of the study suggest that tensor of vastus intermedius is variable and the information provided regarding the attachments, types and quantitative data will contribute to the existing knowledge of the muscle.

World`s Knowledge Spillovers: Beyond Openness and Growth

( C Veeramani ) 세종대학교 경제통합연구소 2014 Journal of Economic Integration Vol.29 No.2

Capital goods industries, for example, nuclear reactors, steam and vapour turbines, air or gas compressors, filtering or purifying machinery and apparatus are intrinsically heterogeneous in terms of vintages and the level of technological knowledge embodied in their products. Countries decide to import wide range of varieties from different sources, which has a bearing on their growth rates. The present paper analyses the hypothesis that the types of imported capital goods and the sources of their origin matter for growth. We construct a new index that measures the level of knowledge embodied in a country’s import basket of capital goods. Using the instrumental variable method, we find that the high initial value of this index for the year 1995, leads to high growth rate of per capita income in the subsequent years during 1995~2005, that is, 10 percent increase in the value of the index raises growth rate by 2 to 3 percentage points. This paper looks beyond the simple relationship between trade openness and growth.

Morphometric evaluation of great vein of Galen and its clinical implications

Grace Suganya. S(Grace Suganya. S ),Ariharan. K(Ariharan. K ),Raveendranath Veeramani(Raveendranath Veeramani ),Dinesh Kumar. V(Dinesh Kumar. V ),Nagarajan Krishnan(Nagarajan Krishnan ) 대한해부학회 2023 Anatomy & Cell Biology Vol.56 No.1

The Galenic venous system plays a vital role in the drainage of blood from deeper parts of the brain. This venous system is contributed by many major veins. These veins are located closer to the pineal gland making the surgical approach in this region difficult. Any accidental injury or occlusion of the vein of Galen could lead to devasting results. Thus, studying the dimensions of the vein of Galen is more important. Hence, we aimed to evaluate the morphometry and trajectory to the vein of Galen. About 100 computed tomographic venography records were evaluated and the length, diameter of vein of Galen, angle between straight sinus and vein of Galen and distance from internal occipital protuberance and roof of fourth ventricle to vein of Galen were studied. The mean length and diameter of vein of Galen were 9.8±2.7 and 4.08±1.04 respectively. The mean angle between straight sinus and vein of Galen was 64.2°. The mean distance between external occipital protuberance and roof of fourth ventricle to vein of Galen were 52±6.9 and 33.3±4.5 respectively. No significant morphometric differences were observed between the age groups as well as between the sexs. The results obtained from this study may be helpful for the neurosurgeons in better understanding of the anatomy of the Galenic venous system and to adopt a safe surgical approach to improve the efficacy of the surgeries of the pineal gland and also in the region of vein of Galen.

Duchenne Muscular Dystrophy and Becker Muscular Dystrophy Confirmed by Multiplex Ligation-Dependent Probe Amplification: Genotype-Phenotype Correlation in a Large Cohort

Seena Vengalil,Veeramani Preethish-Kumar,Kiran Polavarapu,Manjunath Mahadevappa,Deepha Sekar,Meera Purushottam,Priya Treesa Thomas,Saraswathi Nashi,Atchayaram Nalini 대한신경과학회 2017 Journal of Clinical Neurology Vol.13 No.1

Background and Purpose Studies of cases of Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) confirmed by multiplex ligation-dependent probe amplification (MLPA) have determined the clinical characteristics, genotype, and relations between the reading frame and phenotype for different countries. This is the first such study from India. Methods A retrospective genotype-phenotype analysis of 317 MLPA-confirmed patients with DMD or BMD who visited the neuromuscular clinic of a quaternary referral center in southern India. Results The 317 patients comprised 279 cases of DMD (88%), 32 of BMD (10.1%), and 6 of intermediate phenotype (1.9%). Deletions accounted for 91.8% of cases, with duplications causing the remaining 8.2%. There were 254 cases of DMD (91%) with deletions and 25 (9%) due to duplications, and 31 cases (96.8%) of BMD with deletions and 1 (3.2%) due to duplication. All six cases of intermediate type were due to deletions. The most-common mutation was a single-exon deletion. Deletions of six or fewer exons constituted 68.8% of cases. The deletion of exon 50 was the most common. The reading-frame rule held in 90% of DMD and 94% of BMD cases. A tendency toward a lower IQ and earlier wheelchair dependence was observed with distal exon deletions, though a significant correlation was not found. Conclusions The reading-frame rule held in 90% to 94% of children, which is consistent with reports from other parts of the world. However, testing by MLPA is a limitation, and advanced sequencing methods including analysis of the structure of mutant dystrophin is needed for more-accurate assessments of the genotype-phenotype correlation.

Residual Learning of Transfer-learned AlexNet for Image Denoising

Mohan Laavanya,Veeramani Vijayaraghavan 대한전자공학회 2020 IEIE Transactions on Smart Processing & Computing Vol.9 No.2

In today’s scenarios, deep learning has fascinated all researchers from numerous arenas who developed ways to achieve obligatory outcomes. In deep learning, transfer learning is undergoing deep study, because the study helps to practice a pre-trained network for our own tasks. A novel, transfer-learned AlexNet-based residual learning for Gaussian noise reduction is presented in this paper. The method can remove any level of Gaussian noise without having information about the noise variance in both gray scale and color images. Therefore, our technique is blind Gaussian image denoising that learns a residual image by eradicating the clean image from the transfer-learned AlexNet, and removes noise by identifying the difference from the input image. Experimental results with the proposed scheme are compared against a Gaussian denoiser for image denoising in terms of peak signal-to-noise ratio (PSNR) and visual perception. The results have revealed that our residual learning using transfer-learned AlexNet attains promising denoising results.

Reappraisal of arterial anatomy of thumb

Dhivyalakshmi Gnanasekaran,Raveendranath Veeramani,Aravindhan Karuppusamy 대한해부학회 2022 Anatomy & Cell Biology Vol.55 No.4

The nomenclature of arteries supplying the thumb and its sources arteries differs between the studies. This makes difficulty in understanding the irrigation pattern to the thumb. The main purpose of this study was to identify the proper digital arteries supplying the thumb on its radial and ulnar side from both the palmar and dorsal aspect. Also this study aimed to trace its source and classify with proper definition with the review of blood supply to thumb. Dissection was carried out in 55 hands form 28 freshly embalmed adult human cadavers of both genders. The proper digital arteries to the thumb and its source arteries were carefully traced and defined. Thumb receives its dominant blood supply mostly from its palmar side. The ulnar palmar digital artery was seen in all the dissected hand (100.0%) whereas; the radial palmar digital artery was present in 53 hands (96.4%). The radial dorsal digital artery and ulnar dorsal digital artery were observed in only 10.0% and 7.3%. The most common source of both the palmar digital arteries to thumb was from first palmar metacarpal artery (FPMA). In majority of the hands, in addition to the radial or ulnar palmar digital arteries from the FPMA, there were also additional palmar digital arteries arising from the superficial palmar arterial system. The universal naming of the proper digital arteries to the thumb as well as its source arteries is mandatory for the proper understanding of normal as well as variant arterial anatomy of thumb.

Morphometric study of pulleys of the thumb

Dhivyalakshmi Gnanasekaran,Raveendranath Veeramani,Aravindhan Karuppusamy 대한해부학회 2018 Anatomy & Cell Biology Vol.51 No.2

Pulleys are thickened regions in flexor tendons sheaths of the digits. They are essential and act as fulcrum for the flexion and extension of the digits. The arrangement and number of pulley system differs greatly between the thumb and other digits. There is paucity of literature regarding the pulley system of thumb. We aimed to study the morphometry of the pulley system of the thumb in Indian cadavers. Dissection was carried out in 55 adult human cadaveric thumbs. The most common morphologic pattern of pulley observed in the thumb is type III (30 thumbs). The least observed is type I (4 thumbs). The mean width and standard deviation of A1, Av, oblique, and A2 pulleys are 5.06±0.87, 5.38±1.22, 4.68±1.13, and 6.04±1.41 mm, respectively. The gap distances between the pulleys were also measured. The results obtained from the present study may be helpful in surgical treatment of trigger thumb with less complication and also in reconstruction of the closed rupture of the pulley of the thumb.

Image Denoising with a Convolution Neural Network using Gaussian Filtered Residuals

Laavanya Mohan,Vijayaraghavan Veeramani 대한전자공학회 2021 IEIE Transactions on Smart Processing & Computing Vol.10 No.2

Deep learning using a convolutional neural network has become a state-of-art technique in image processing. In recent scenarios, image denoising using a residual image in deep learning has been popular. However, one aspect missing in these methods is that the residual image has all the noise and very small structured details of the input image. Therefore, we have developed a Gaussian filter residual convolutional neural network architecture for color image denoising. Gaussian residual learning was used to boost the denoising performance. The architecture is designed to remove additive white Gaussian noise, which is one of the most basic types of noise that affects an image when captured. The network with Gaussian residual learning removes the clean image using the features learned from the hidden layer. The peak signal-to-noise ratio and structural similarity index measure achieved by our method reveals that the presented approach is better at denoising images with Gaussian noise than a convolutional neural network.