Qualification: 
Ph.D, M.Tech, B-Tech
Email: 
ushadeviammac@am.amrita.edu

Dr. Ushadevi Amma C. has been a Professor in the Department of Electronics and Communication Engineering at the Amritapuri Campus, since July 2021. She holds B. Tech from University of Kerala ( T.K.M. College of Engineering). M Tech in Instrumentation from the Indian Institute of Technology, Kharagpur and Ph. D. in Instrumentation Engineering from the Indian Institute of Science, Bangalore.

Dr. Ushadevi Amma C. joined Amrita Vishwa Vidyapeetham after serving in various academic and administrative positions at T.K.M College of Engineering, Kollam, from August 1990 to April 2021, including Head, Department of Electrical and Electronic Engineering and Dean of Undergraduate Studies, with two years of prior industrial experience. She served as a member of the board of studies in Engineering (both UG and PG) and the convener of the syllabus revision committee at the University of Kerala, as well as a member of the academic review committee at APJ Abdul Kalam Kerala Technological University. She was an invited teacher for the Indian Academy of Sciences and a mentor for the MHRD's INSPIRE Program at the national level. She is a life member of ISTE, a senior member of IEEE, and currently serving as Treasurer, IEEE Education Society, Kerala Chapter.

Her research interests include  biomedical instrumentation, medical instrument development  and medical imaging. Presently guiding 3 Ph. D. students at APJ Abdul Kalam Technological University, undertaking collaborative research, with the Dept. of Radiology, Sree Chitra Tirunal Institute for Medical Sciences & Technology, Thiruvananthapuram, on novel MR imaging approaches that do not require the use of contrast agents. She developed “Ultrasound assisted Optical Elastography,” a radiation-free approach for the early detection of breast cancer, as part of her Ph. D. study at IISc, Bangalore. As part of the M Tech project, she developed an “Infant Apnea monitor using impedance Pneumography and this work was recognised with the L & T- ISTE Best M Tech thesis award in 1997.

Publications

Publication Type: Conference Paper

Year of Publication Title

2020

Shafna V., Jini Raju, Ansamma John, and Ushadevi Amma C., “Values and Count Optimization of IVIM diffusion Weighting Parameter”, in 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS), Thoothukudi, India, 2020.[Abstract]


IntraVoxel Incoherent Motion (IVIM) based Magnetic Resonance Imaging (MRI) has gained popularity in the field of medical diagnosis in recent times. The IVIM principle distinguishes the effect of perfusion and diffusion in biological tissues in a non-invasive manner, without injecting any contrast agents to the body tissues. The pathological conditions can be quantitatively determined by IVIM parameters and for the proper estimation of these parameters, the MRI signal must be acquired with several diffusion weightings, b. The b value distributions used so far are heuristic and show broad differences between researchers. In this analysis, the effect of b values on the acquisition of IVIM data is evaluated and the optimal distribution of b values is determined using a genetic algorithmic method. Our result generates 10 b value distributions as 0, 10, 10, 20, 30, 70, 80, 110, 120 and 500 and this distribution has worked well and can greatly decrease the overall measurement error. The overall parameter efficiency relies heavily on the Signal to Noise(SNR): for a lower SNR value, the error on parameter estimation is far higher than the error for a higher SNR value.

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2020

Thushara A., Ushadevi Amma C., Ansamma John, and Reshma Saju, “Multimodal MRI Based Classification and Prediction of Alzheimer’s Disease Using Random Forest Ensemble”, in 2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA), Cochin, India, 2020.[Abstract]


Alzheimer's disease (AD) is a neurodegenerative disorder that affects millions of people worldwide and it accounts for a significant decrease in the quality of life of patients and their families. Currently, available treatment options for AD is merely palliative and no drugs are available for the inexorable progression of the disorder that is diagnosed during the later stage of the disease. So the early diagnosis of AD is an optimal strategy in formulating the treatment plan. Neuroimaging modalities like Magnetic Resonance Imaging (MRI), resting-state functional Magnetic resonance imaging (rs-fMRI), Diffusion Tensor Imaging (DTI) and Positron emission tomography (PET) are used to diagnose the structural and functional alteration caused by AD. For the past few years, machine learning methods are widely used to analyze the neuroimaging data acquired from MRI imaging modalities for the diagnosis and prediction of neurological disorder. In this work, the random forest classification algorithm is used to classify and predict Alzheimer's disease. The data set that is used in this study is TADPOLE data set, which has been acquired from Alzheimer's neuroimaging Initiative (ADNI). In this work, the multiclass classification that distinguishes the different level of Alzheimer's disease has achieved an accuracy comparable to current research in the prediction of AD.

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2020

S. A., Ushadevi Amma C., Ansamma John, and Athira B., “Effects of Preprocessing on the Quantification of Cerebral Blood Flow from Arterial Spin Labeling MRI”, in 2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA), Cochin, India, 2020.[Abstract]


Magnetic Resonance Imaging (MRI) using Arterial Spin Labeling (ASL) is a quantitative Imaging technique which is used to quantify Cerebral Blood Flow (CBF) and it plays a vital role as a bio-marker for various neuro-degenerative diseases and brain tumour. The ASL images suffer from low Signal-to-Noise Ratio (SNR) and low resolution, which can be improved by acquiring a number of ASL raw images called label and control images. Acquiring large number of images, results in prolonged scanning time, which in turn leads to different artifacts in ASL images. Hence different image preprocessing techniques are essential for the accurate quantification of CBF values. Moreover, there is no standard procedure for processing ASL data due to the large number of assumptions and various parameters involved in CBF quantification. The proposed research work analyses the effects of different preprocessing stages on CBF quantification on pulsed ASL (PASL) and Pseudo continuous ASL (PCASL) data. The use of an outlier detection SCORE+ algorithm with and without preprocessing stages are also examined.

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2020

Jini Raju, Ushadevi Amma C., Ansamma John, and Anagha D. Raj, “Study on the effect of Denoising Algorithms on the parametric maps of IVIM Imaging”, in 8th International Conference on Innovations in Computer Science and Engineering, (ICISE-2020) , 2020.[Abstract]


Intra Voxel Incoherent Motion Magnetic Resonance Imaging (IVIM-MRI) is a quantitative imaging method used for the diagnosis of pathological disorders. The accuracy of the parameters derived from the IVIM images significantly affects the precision of diagnosis. Many researches are in progress in this area, aiming the improvement of the accuracy of IVIM parameters. The accuracy of IVIM parameters is affected by the presence of noise in IVIM images, which results in poor Signal to Noise Ratio (SNR). The noise effect becomes more significant in IVIM images where high diffusion weights are used. The proposed work is a preliminary study to analyze the effect of various denoising filters applied to the noisy parametric maps derived from IVIM images. The Gaussian smoothing filter, Non local Means filter (NLM), Anisotropic Diffusion filter (AD) and Bilateral filter are considered for comparison. The results show that, denoising the parametric maps will improve the signal intensity and it is observed that NLM filter shows better results in terms of both qualitative and quantitative metrics. Moreover, our work proved that the experimentation studies in phantom data is valid and can be used in the absence of adequate number of clinical IVIM dataset.

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2007

Ushadevi Amma C. and R. Sreekumari Bharat Chandran, “Remote palpation with a focused ultrasound beam: An optical read-out using a multi-wavelength scheme for separating the contribution from amplitude of vibration and absorption coefficient”, in Saratov Fall meeting,Saratov, Russia, 2007.

2007

Ushadevi Amma C., R. Sreekumari Bharat Chandran, R. Mohan Vasu, and Ajay K. Sood, “Elasticity mapping of tissue mimicking phantoms by remote palpation with a focused ultrasound beam and intensity autocorrelation measurements”, in Saratov Fall Meeting 2006: Optical Technologies in Biophysics and Medicine VIII, 2007.[Abstract]


We use a focused ultrasound beam to load a region of interest (ROI) in a tissue-mimicking phantom and read out the vibration amplitude of phantom particles from the modulation depth in the intensity autocorrelation of a coherent light beam that intercepted the ROI. The modulation depth, which is also affected by the local light absorption coefficient, which is employed in ultrasound assisted optical tomography, to read out absorption coefficient is greatly influenced by the vibration amplitude, depends to a great extend on local elasticity. We scan a plane in an elastography phantom with an inhomogeneous inclusion, in elasticity with the focused ultrasound and from the measured modulation depth variation create a qualitative map of the elasticity variation in the interrogated plane.

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2006

Ushadevi Amma C., R. Sreekumari Bharat Chandran, R. Mohan Vasu, and Ajay K. Sood, “Elastic property estimation using ultrasound assisted optical elastography through remote palpation-A simulation study”, in Saratov Fall Meeting 2005: Coherent Optics of Ordered and Random Media VI, 2006.[Abstract]


We propose an effective elastography technique in which an acoustic radiation force is used for remote palpation to generate localized tissue displacements, which are directly correlated to localized variations of tissue stiffness and are measured using a light probe in the same direction of ultrasound propagation. The experimental geometry has provision to input light beam along the ultrasound propagation direction, and hence it can be prealigned to ensure proper interception of the focal region by the light beam. Tissue-mimicking phantoms with homogeneous and isotropic mechanical properties of normal and malignant breast tissue are considered for the study. Each phantom is insonified by a focusing ultrasound transducer (1 MHz). The focal volume of the transducer and the ultrasound radiation force in the region are estimated through solving acoustic wave propagation through medium assuming average acoustic properties. The forward elastography problem is solved for the region of insonification assuming the Lame's parameters and Poisson's ratio, under Dirichlet boundary conditions which gives a distribution of displacement vectors. The direction of displacement, though presented spatial variation, is predominantly towards the ultrasound propagation direction. Using Monte Carlo (MC) simulation we have traced the photons through the phantom and collected the photons arriving at the detector on the boundary of the object in the direction of ultrasound. The intensity correlations are then computed from detected photons. The intensity correlation function computed through MC simulation showed a modulation whose strength is found to be proportional to the amplitude of displacement and inversely related to the storage (elastic) modulus. It is observed that when the storage modulus in the focal region is increased the computed displacement magnitude, as indicated by the depth of modulation in the intensity autocorrelation, decreased and the trend is approximately exponential.

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2005

Ushadevi Amma C., R. Sreekumari Bharat Chandran, R. Mohan Vasu, and Ajay K. Sood, “Application of Diffusing wave spectroscopy to measure the visco-elastic property of breast tissue mimicking materials”, in Proceedings of International conference on optics and optoelectronics, Dehradun, 2005.

2001

Ushadevi Amma C. and Niranjan D. Khambete, “Problems encountered with apnea monitor using Impedance Pneumography”, in Proceedings of Twenty fourth National systems conference, 2001.

1997

Ushadevi Amma C. and Srinivasu Maka, “APNEA monitor for infants using Impedance Pneumography”, in Proceedings of Twenty first National systems conference, 1997.

Publication Type: Journal Article

Year of Publication Title

2020

Jini Raju, Ushadevi Amma C., and Ansamma John, “A novel approach for b-value optimization in Intravoxel Incoherent Motion Imaging using Metaheuristic algorithm”, Expert Systems with Applications, vol. 168, p. 114270, 2020.[Abstract]


Intravoxel Incoherent Motion (IVIM) based Magnetic Resonance Imaging (MRI) technique allows the quantitative evaluation of perfusion and diffusion without the use of contrast agents. The correctness of the diagnosis depends upon the accuracy and precision of IVIM parameter estimation. To achieve this, several diffusion weighted images must be acquired. The criteria of selection of diffusion weights varies among researchers. The diffusion weights are incorporated by a factor called ‘b value’, which reflects the intensity and duration of the diffusion gradient pulses used for imaging. IVIM imaging takes more time for image acquisition with multiple b values and the selection of the absolute b values as well as the number of b values, is a real challenge. As the b value count increases the scan time increases, which leads to increased patient discomfort and motion artifacts, resulting in poor image quality. Moreover, in most cases, these b values are found using trial and error methods during image acquisition. These issues can be addressed to a large extent by finding, optimum number and range of b values. In this paper, we propose a population based Metaheuristic algorithm for arriving at the optimal b value count and the range of absolute b values for liver, which is an organ with high perfusion. Three separate models are developed to appropriately choose all possible b values ranging between 0 s/mm2 and 850 s/mm2, to observe the effects of diffusion and perfusion as well as to increase the global search space. The effect of low (0 s/mm2 to 50 s/mm2 ), medium (55 s/mm2 to 220 s/mm2) and high (230 s/mm2 to 800 s/mm2) b values has been studied to find the optimal number of b values that can be used for IVIM imaging. In order to define a b value count that minimizes the error in IVIM parameters, simulation experiments are performed for different b value counts specifically 16, 14, 12, 10, 8, 6 and 4. For each of these experiments, repeated observations are made to analyze the parameter uncertainty. The results obtained show that the b value count can be minimized for a better quantitative estimation of IVIM parameters with the least possible errors and the difference in error between each of these observations is found to be less than 0.001. Minimization of b value count results in the reduction of overall image acquisition time and hence patient discomfort. It is also observed that for a very good SNR, b value count can be reduced to 4 although for a reasonable SNR, 8 or 10 b values are to be used for accurate quantitative estimation of IVIM parameters.

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2011

R. Sriram Chandran, Debasish Roy, Rajan Kanhirodan, Ram Mohan Vasu, and Ushadevi Amma C., “Ultrasound modulated optical tomography: Young's modulus of the insonified region from measurement of natural frequency of vibration.”, Opt Express, vol. 19, no. 23, pp. 22837-50, 2011.[Abstract]


We demonstrate a method to recover the Young's modulus (E) of a tissue-mimicking phantom from measurements of ultrasound modulated optical tomography (UMOT). The object is insonified by a dual-beam, confocal ultrasound transducer (US) oscillating at frequencies f₀ and f₀ + Δf and the variation of modulation depth (M) in the autocorrelation of light traversed through the focal region of the US transducer against Δf is measured. From the dominant peaks observed in the above variation, the natural frequencies of the insonified region associated with the vibration along the US transducer axis are deduced. A consequence of the above resonance is that the speckle fluctuation at the resonance frequency has a higher signal-to-noise to ratio (SNR). From these natural frequencies and the associated eigenspectrum of the oscillating object, Young's modulus (E) of the material in the focal region is recovered. The working of this method is confirmed by recovering E in the case of three tissue-mimicking phantoms of different elastic modulus values.

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2008

Ushadevi Amma C. and R. Sreekumari Bharat Chandran, “Ultrasound assisted optical elastography - Novel technique for the early detection of breast cancer”, International Journal of Functional Informatics and Personalised Medicine, 2008.

2008

Ushadevi Amma C., R. Sreekumari Bharat Chandran, R. Mohan Vasu, and Ajay K. Sood, “Detection of optical and mechanical property inhomogeneities in tissue mimicking phantoms using an ultrasound assisted optical probe.”, J Biomed Opt, vol. 13, no. 6, p. 064025, 2008.[Abstract]


We discuss the issue of separating contributions from mechanical and optical properties of a moderately scattering tissue phantom to the modulation depth (M) of intensity autocorrelation measured in an ultrasound-assisted optical tomography system using axial and transverse illuminations. For axial illumination, M is affected by both the displacement and absorption coefficient, more prominently by displacement. But transverse illumination has very little contribution from displacement of scattering centers. Since displacement is related to the elastic property of the insonified region, we show that there is a possibility of separating the contributions from elastic and optical properties of the insonified region using axial and transverse illuminations. The main conclusions of our study using moderately scattering phantoms are: 1. axial illumination is the best for mapping storage modulus inhomogeneities, but M is also affected by optical absorption; 2. transverse illumination is the best for mapping absorption inhomogeneities; and 3. for the practically relevant case of an inclusion with larger storage modulus and absorption, both illuminations produced large contrast in M. When the scattering coefficient is high, the angle dependence of illumination is lost and the present method is shown to fail to separate these contributions based on direction of illumination.

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2007

R. Sreekumari Bharat Chandran, Ushadevi Amma C., R. Mohan Vasu, and Ajay K. Sood, “Ultrasound assisted optical elastography for measurement of tissue stiffness: contribution to the measurement from scattering coefficient variation”, Saratov Fall Meeting 2006: Optical Technologies in Biophysics and Medicine VIII, 2007.[Abstract]


In ultrasound assisted optical elastography (UAOE) the amplitude of vibration inside the object introduced by an ultrasound (US) beam is read out by a coherent light beam. The measurement is the depth of modulation in the intensity autocorrelation of light that intercepted the insonified region and detected at the boundary. It is observed that the measured depth of modulation is owing to refractive index modulation and scattering coefficient modulation, in addition to the tissue-particle vibration. Since elasticity is measured from the amplitude of vibration it is essential to characterize and separate the contribution to the modulation from refractive index and scattering coefficient modulations. In this work we report the contribution of the scattering coefficient modulation in the insonified region to the measured modulation in the autocorrelation. We found through simulation studies that the contribution from scattering coefficient is small compared to the vibration. In addition, this contribution becomes smaller as the stiffness in the region increases. We also provide a means of quantifying this contribution so that the effect of vibration amplitude can be separated from the overall measured modulation depth.

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2007

Ushadevi Amma C., R. Sreekumari Bharat Chandran, R. Mohan Vasu, and Ajay K. Sood, “Mechanical property assessment of tissue-mimicking phantoms using remote palpation and optical read-out for amplitude of vibration and refractive index modulation.”, J Biomed Opt, vol. 12, no. 2, p. 024028, 2007.[Abstract]


A coherent light beam is used to interrogate the focal region within a tissue-mimicking phantom insonified by an ultrasound transducer. The ultrasound-tagged photons exiting from the object carry with them information on local optical path length fluctuations caused by refractive index variations and medium vibration. Through estimation of the force distribution in the focal region of the ultrasound transducer, and solving the forward elastography problem for amplitude of vibration of tissue particles, we observe that the amplitude is directed along the axis of the transducer. It is shown that the focal region interrogated by photons launched along the transducer axis carries phase fluctuations owing to both refractive index variations and particle vibration, whereas the photons launched perpendicular to the transducer axis carry phase fluctuations arising mainly from the refractive index variations, with only smaller contribution from vibration of particles. Monte-Carlo simulations and experiments done on tissue-mimicking phantoms prove that as the storage modulus of the phantom is increased, the detected modulation depth in autocorrelation is reduced, significantly for axial photons and only marginally for the transverse-directed photons. It is observed that the depth of modulation is reduced to a significantly lower and constant value as the storage modulus of the medium is increased. This constant value is found to be the same for both axial and transverse optical interrogation. This proves that the residual modulation depth is owing to refractive index fluctuations alone, which can be subtracted from the overall measured modulation depth, paving the way for a possible quantitative reconstruction of storage modulus. Moreover, since the transverse-directed photons are not significantly affected by storage modulus variations, for a quantitatively accurate read-out of absorption coefficient variation, the interrogating light should be perpendicular to the focusing ultrasound transducer axis.

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2007

Ushadevi Amma C., R. Sreekumari Bharat Chandran, R. Mohan Vasu, and Ajay K. Sood, “Measurement of visco-elastic properties of breast-tissue mimicking materials using diffusing wave spectroscopy.”, J Biomed Opt, vol. 12, no. 3, p. 034035, 2007.[Abstract]


Diffusing wave spectroscopy (DWS), without the use of tracer particles, has been used to study the internal dynamics of polyvinyl alcohol (PVA) phantoms, which mimic the properties of normal and malignant breast tissues. From the measured intensity autocorrelations, the mean square displacement (MSD) of phantom meshing is estimated, leading to the storage and loss moduli of the medium covering frequencies up to 10 KHz. These are verified with independent measurements from a dynamic mechanical analyzer (DMA) at low frequencies. We thus prove the usefulness of DWS to extract visco-elastic properties of the phantom and its possible application in detecting malignancy in soft tissues.

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2006

Ushadevi Amma C., R. Mohan Vasu, and Ajay K. Sood, “Application of ultrasound-tagged photons for measurement of amplitude of vibration of tissue caused by ultrasound: theory, simulation, and experiments.”, J Biomed Opt, vol. 11, no. 3, p. 34019, 2006.[Abstract]


We investigate the modulation of an optical field caused by its interaction with an ultrasound beam in a tissue mimicking phantom. This modulation appears as a modulation in the intensity autocorrelation, which is measured by a photon counting correlator. The factors contributing to the modulation are: 1. amplitude of vibration of the particles of the tissue, 2. refractive index modulation, and 3. absorption coefficient in the region of the tissue intercepted by the ultrasound beam and light. We show in this work that a significant part of the contribution to this modulation comes from displacement of the tissue particles, which in turn is governed by the elastic properties of the tissue. We establish, both through simulations and experiments using an optical elastography phantom, the effects of the elasticity and absorption coefficient variations on the modulation of intensity autocorrelation. In the case where there is no absorption coefficient variation, we suggest that the depth of modulation can be calibrated to measure the displacement of tissue particles that, in turn, can be used to measure the tissue elasticity.

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2005

Ushadevi Amma C., R. Mohan Vasu, and Ajay K. Sood, “Design, fabrication, and characterization of a tissue-equivalent phantom for optical elastography.”, J Biomed Opt, vol. 10, no. 4, p. 44020, 2005.[Abstract]


We suitably adapt the design of a tissue-equivalent phantom used for photoacoustic imaging to construct phantoms for optical elastography. The elastography phantom we consider should have optical properties such as scattering coefficient, scattering anisotropy factor, and refractive index; mechanical properties such as storage and loss modulus; and acoustic properties such as ultrasound velocity, attenuation coefficient, and acoustic impedance to match healthy and diseased tissues. The phantom is made of poly (vinyl alcohol) (PVA) and its mechanical, optical, and acoustic properties are tailored by physical cross-linking effected through subjecting a suitable mix of PVA stock and water to a number of freeze-thaw cycles and by varying the degree of hydrolysis in the PVA stock. The optical, mechanical, and acoustic properties of the samples prepared are measured by employing different techniques. The measured variations in the values of optical scattering coefficient, scattering anisotropy factor, and refractive index and storage modulus are found to be comparable to those in normal and diseased breast tissues. The acoustic properties such as sound speed, acoustic attenuation coefficient, and density are found to be close to the average values reported in the literature for normal breast tissue.

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