Titas De
Microsoft Research, Outlook Search, Department Member
- Indian Institute of Technology Kharagpur, Electrical Engineering and Computer Science, Department MemberStanford University, Psychiatry and Behavioral Sciences, Department Memberadd
Bone fragility and fracture caused by osteoporosis or injury are prevalent in adults over the age of 50 and can reduce their quality of life. Hence, predicting the biomechanical bone strength, specifically of the proximal femur, through... more
Bone fragility and fracture caused by osteoporosis or injury are prevalent in adults over the age of 50 and can reduce their quality of life. Hence, predicting the biomechanical bone strength, specifically of the proximal femur, through non-invasive imaging-based methods is an important goal for the diagnosis of Osteoporosis as well as estimating fracture risk. Dual X-ray absorptiometry (DXA) has been used as a standard clinical procedure for assessment and diagnosis of bone strength and osteoporosis through bone mineral density (BMD) measurements. However, previous studies have shown that quantitative computer tomography (QCT) can be more sensitive and specific to trabecular bone characterization because it reduces the overlap effects and interferences from the surrounding soft tissue and cortical shell. This study proposes a new method to predict the bone strength of proximal femur specimens from quantitative multi-detector computer tomography (MDCT) images. Texture analysis metho...
Research Interests: Engineering, Computer Science, Artificial Intelligence, Computer Vision, Image Processing, and 15 moreMedical Imaging, Machine Learning, Digital Image Processing, Anisotropy, Femur, Digital Signal and Image Processing, Anisotropic Diffusion, Human Femur, Bone Mineral Density, Anisotropic, Femur BMD, Minkowski, Femur Neck, Computer Aided Diagnosis, and arXiv
We have developed a system for automatic facial expression recognition, which runs on Google Glass and delivers real-time social cues to the wearer. We evaluate the system as a behavioral aid for children with Autism Spectrum Disorder... more
We have developed a system for automatic facial expression recognition, which runs on Google Glass and delivers real-time social cues to the wearer. We evaluate the system as a behavioral aid for children with Autism Spectrum Disorder (ASD), who can greatly benefit from real-time non-invasive emotional cues and are more sensitive to sensory input than neurotypically developing children. In addition, we present a mobile application that enables users of the wearable aid to review their videos along with auto-curated emotional information on the video playback bar. This integrates our learning aid into the context of behavioral therapy. Expanding on our previous work describing in-lab trials, this paper presents our system and application-level design decisions in depth as well as the interface learnings gathered during the use of the system by multiple children with ASD in an at-home iterative trial.
Research Interests: Computer Science, Artificial Intelligence, Human Computer Interaction, Computer Vision, Image Processing, and 15 moreAutism, Autism Spectrum Disorders, Face Recognition, Facial expression, Digital Image Processing, Face Detection, Face emotion detection, Facial Expressions and Emotions, Emotion Recognition, Human Mobile Interaction, Face Detection and Recognition, Human Interactions With Social Mobile Technologies, Image Processing With Artificial Intelligence, Autism Spectrum Treatment, and Design for Autism
In recent years, much focus has been put on employing technology to make novel behavioural aids for those with autism. Most of these are digital adaptations of tools used in standard behavioural therapy to enforce normative skills. These... more
In recent years, much focus has been put on employing technology to make novel behavioural aids for those with autism. Most of these are digital adaptations of tools used in standard behavioural therapy to enforce normative skills. These digital counterparts are often used outside of both the larger therapeutic context and the real world, in which the learned skills might apply. To address this, we are designing a system of automatic expression recognition on wearable devices that integrates directly into the families daily social interactions, to give children and their caregivers the tools and information they need to design their own holistic therapy. In order to develop a tool that will be truly useful to families, we proactively include children with autism and their families as co-designers in the development process. By providing an app and interface with interchangeable social feedback options, we aim to produce a framework for therapy that folds into their daily lives, tail...
Research Interests: Artificial Intelligence, Computer Vision, Autism, Autism Spectrum Disorders, Face Recognition, and 15 moreFacial expression, Face Detection, Android, Development on Android platform, Android Development, Facial Expression Analysis, Designing SW for children with autism, Facial expression in clinical groups and psychotherapy, Face Detection and Recognition, Facial Expression and Body Language, Facial Animation, Android Programming, Autism Perception and Design, Autism Spectrum Treatment, and Design for Autism
Research Interests: Computer Science, Artificial Intelligence, Human Computer Interaction, Computer Vision, Image Processing, and 15 moreAutism, Autism Spectrum Disorders, Face Recognition, Facial expression, Digital Image Processing, Face Detection, Face emotion detection, Facial Expressions and Emotions, Emotion Recognition, Human Mobile Interaction, Face Detection and Recognition, Human Interactions With Social Mobile Technologies, Image Processing With Artificial Intelligence, Autism Spectrum Treatment, and Design for Autism
Research Interests:
Research Interests: Engineering, Computer Science, Artificial Intelligence, Computer Vision, Image Processing, and 15 moreMedical Imaging, Machine Learning, Digital Image Processing, Anisotropy, Femur, Digital Signal and Image Processing, Anisotropic Diffusion, Human Femur, Bone Mineral Density, Anisotropic, Femur BMD, Minkowski, Femur Neck, Computer Aided Diagnosis, and arXiv
Research Interests: Engineering, Computer Science, Computer Vision, Biomedical Engineering, Computed Tomography, and 15 moreBioMedical Physics, Biomedical signal and image processing, Digital Image Processing, Anisotropy, Feature Selection, Biomedical Imaging, Femur, Diagnosis, Feature Extraction, Histogram Comparison, Histogram, Damage and failure mechanism under impact loading, Computer Aided Detection and Diagnosis for Medical Images, Biomechanical Indicators, and Computer Aided Diagnosis
Research Interests:
Systems for monitoring blood loss include a display for simultaneously depicting a current blood loss metric at different time points or along a time line. In addition, historical or comparative blood loss information is provided on the... more
Systems for monitoring blood loss include a display for simultaneously depicting a current blood loss metric at different time points or along a time line. In addition, historical or comparative blood loss information is provided on the display so that the healthcare provider can see assess the current blood loss metric relative to other metrics, so that the healthcare provider can more accurately assess and manage the patient's status.
Research Interests: Computer Vision, Machine Learning, Surgical Education, Object Recognition (Computer Vision), Python, and 24 moreC++ Programming, iPad, Thermal Imaging, Ipad for online learning, Ipad in the classroom, Social Mobile Devices as Tools for Qualitative Research in Education: iPhones and iPads in Ethnography, Interviewing, and Design-Based Research, iOS Application Development, Apple IOS, iPad use in the classroom, iPads in education, Surgical Procedures, iPads, Iphones, Objective-C, Objective C, Ipads in the classroom, Iphone5, IPads, FLIR, iTunes App Store, Ipad App Developers, App Store, ios Swift Programming, and Thermal Imaging in Medicine
A system and method for assessing the concentration of a fluid component within a container, the method comprising: receiving data associated with an image of the canister from the image, detecting a color grid comprising color elements... more
A system and method for assessing the concentration of a fluid component within a
container, the method comprising: receiving data associated with an image of the canister from the image, detecting a color grid comprising color elements coupled to the canister selecting a region of the image corresponding to a portion of the canister; determining a match between a detected color of the region and a shade in the set of colors associated with the color grid captured in the image; based upon a position of a color element corresponding to the shade in the color grid, retrieving a concentration of the blood component associated with the shade of color.
container, the method comprising: receiving data associated with an image of the canister from the image, detecting a color grid comprising color elements coupled to the canister selecting a region of the image corresponding to a portion of the canister; determining a match between a detected color of the region and a shade in the set of colors associated with the color grid captured in the image; based upon a position of a color element corresponding to the shade in the color grid, retrieving a concentration of the blood component associated with the shade of color.
Research Interests: Human Computer Interaction, Surgery, Computer Vision, Image Processing, Machine Learning, and 46 moreClassification (Machine Learning), Object Recognition (Computer Vision), Applications of Machine Learning, Python, Digital Image Processing, iPad, Color Perception, OpenCv or Computer Vision, Automatic Classification (Machine Learning), Infrared spectroscopy, Image Processing with OpenCV, Thermal Imaging, Computer Vision, Document Image Analysis, Machine Learning, Non Parametric Estimation, iOS Application Development, Image Segmentation, Skin Color, Bayesian Networks, Machine Learning and Pattern Recognition, Color Image Segmentation, Apple IOS, Python Programming, Infrared Images, FDA, iPads, Infrared Thermography, OpenCV, Iphones, Fda Regulations and Policies, Support Vector Machines (SVMs), Image Processing and Multimedia, Visual Estimation of Blood Loss, Thermal Imagery, Machine Learning Big Data, Illuminant Estimation, Parametric Estimation, Blood Loss, Food and Drug Administration, FDA Approval, US FDA approval process, Thermal Imager, FDA Software Validation, Keypoint Descriptor, ios Swift Programming, Image Color Analysis, Thermal Imaging in Medicine, Food and Drug Administration (FDA), and FDA Compliance
We have developed a system for automatic facial expression recognition running on Google Glass, delivering real-time social cues to children with Autism Spectrum Disorder (ASD). The system includes multiple mechanisms to engage children... more
We have developed a system for automatic facial expression recognition running on Google Glass, delivering real-time social cues to children with Autism Spectrum Disorder (ASD). The system includes multiple mechanisms to engage children and their parents, who administer this technology within the home. We completed an at-home design trial with 14 families that used the learning aid over a 3-month period. We found that children with ASD generally respond well to wearing the system at home and opt for the most expressive feedback choice. We further evaluated app usage, facial engagement, and model accuracy. We found that the device can act as a powerful training aid when used periodically in the home, that interactive video content from wearable therapy sessions should be augmented with sufficient context about the content to produce long-term engagement, and that the design of wearable systems for children with ASD should be heavily dependent on the functioning level of the child. We contribute general design implications for developing wearable aids used by children with ASD and other behavioral disorders as well as their parents during at-home parent-administered therapy sessions.
Research Interests: Cognitive Behavioral Therapy, Artificial Intelligence, Human Computer Interaction, Computer Vision, Image Processing, and 72 moreWeb Design, Facial Recognition, Machine Learning, Autism, Wearable Computing, Autism Spectrum Disorders, Pattern Recognition, Face Recognition, Object Recognition (Pattern Recognition), Human-Computer Interaction for Games, Wearable Technologies, Micro Facial Expressions, Autism and creativity, Pattern recognition (Engineering), FACS (Facial Action Coding System), Facial expression, Applied Behavior Analysis, Autism (Education), Facial Action Coding System (FACS), Tangibles User Interfaces and Autism, Autism and Language, Pattern Recognition and Classification, Wearable sensors, Human-Computer Interface, Pattern Recognition and Image processing, Facial expressions, Teaching Students with Autism, Facial Expressions and Emotions, Autism and its psychological and early intervention, Computer Vision and Pattern Recognition, Emotion Recognition, Wearable Technology, Wearable computers, Human Computer Interaction Design, Machine Learning and Pattern Recognition, Intellectual & Developmental Disabilities and Autism Spectrum Disorders, Facial Expression Analysis, Autism Spectrum Disorder, Behavioral Disorders, Facial expression in clinical groups and psychotherapy, Aspergers and High Functioning Autism, Applications of Machine Learning and Pattern Recognition · NLP · Computer vision, medical imaging · Bioinformatics, medical knowledge discovery · Machine learning-based algorithms in wireless networking, Pattern Recognization, Facial Expression and Body Language, Wearables, Signal and Image Processing, Pattern Recognition, Machine learning, Feature Extraction and Classification of Biomedical signals, Brain Machine Interface (BMI), and Computational Neuroscience, Statistical Pattern Recognition, Applied Behavioral Analysis, Behavioral Pattern Recognition, Ubiquitous Technologies, Parenting and Autism, Image Processing & Pattern Recognition, Google Glass, Pattern Recogntion, Ubiquitous Technology, Expression analysis, Histogram of Gradient, Wearable Devices, Facial Expression Recognition, Autism Spectrum Treatment, Human-Computer Interaction, Machine Learning & Data Mining In Pattern Recognition, Facial Expressions Analysis, Histogram of Oriented Gradient, Design for Autism, Micro-expressions, Automatic facial expression analysis, Emotive Wearables, Histograms of Oriented Gradients, Autism-Friendly Design, HoloLens, and Histograms of Oriented Gradients (HOG)
Osteoporosis is characterized by changes to the trabecular bone micro-architecture in addition to reduction in bone mineral density (BMD). This study proposes using anisotropic Minkowski Functionals (AMF) for characterizing trabecular... more
Osteoporosis is characterized by changes to the trabecular bone micro-architecture in addition to reduction in bone mineral density (BMD). This study proposes using anisotropic Minkowski Functionals (AMF) for characterizing trabecular bone micro-architecture and evaluates their ability at predicting bone strength when analyzed with support vector regression (SVR).
Research Interests:
The ability of Anisotropic Minkowski Functionals (AMFs) to capture local anisotropy while evaluating topological properties of the underlying gray-level structures has been previously demonstrated. We evaluate the ability of this approach... more
The ability of Anisotropic Minkowski Functionals (AMFs) to capture local anisotropy while evaluating topological properties of the underlying gray-level structures has been previously demonstrated. We evaluate the ability of this approach to characterize local structure properties of trabecular bone micro-architecture in ex vivo proximal femur specimens, as visualized on multi-detector CT, for purposes of biomechanical bone strength prediction. To this end, volumetric AMFs were computed locally for each voxel of volumes of interest (VOI) extracted from the femoral head of 146 specimens. The local anisotropy captured by such AMFs was quantified using a fractional anisotropy measure; the magnitude and direction of anisotropy at every pixel was stored in histograms that served as a feature vectors that characterized the VOIs. A linear multi-regression analysis algorithm was used to predict the failure load (FL) from the feature sets; the predicted FL was compared to the true FL determined through biomechanical testing. The prediction performance was measured by the root mean square error (RMSE) for each feature set. The best prediction performance was obtained from the fractional anisotropy histogram of AMF Euler Characteristic (RMSE = 1.01 ± 0.13), which was significantly better than MDCT-derived mean BMD (RMSE = 1.12 ± 0.16, p<0.05). We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding regional trabecular bone quality and contribute to improved bone strength prediction, which is important for improving the clinical assessment of osteoporotic fracture risk.
Research Interests: Computer Vision, Biomedical Engineering, Image Processing, Medical Imaging, Computed Tomography, and 44 moreMachine Learning, BioMedical Physics, Medical Image Processing, Computer-Aided Diagnosis, Image Features Extraction, Support Vector Machines, Medical Physics, Biomedical signal and image processing, Regression Models, Matlab, Digital Image Processing, Anisotropy, Feature Selection, Biomedical Imaging, Matlab Programming, Osteoporosis, Diagnosis, Regression, Support Vector Regression, MATLAB code, Regression Analysis, Feature Extraction, Machine Learning, Classification, Support Vector Machine, Histogram Comparison, Multiple Linear Regression, Histogram, Medical Diagnosis, Osteoporotic fractures, Matlab & Simulink programming, Support Vector Machines (SVMs), Damage and failure mechanism under impact loading, Multiple regression analysis, Volume of Interest, Computer Aided Detection and Diagnosis for Medical Images, Osteoporosis Treatment, RMSE, Linear Regression, Osteoporosis Diagnosis, Biomechanical Indicators, Medical Diagnosis System, Histogram of Gradient, Medical Diagnostics, Minkowski Space, and Histogram of Oriented Gradient
The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a... more
The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10-4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications.