Titas De | Microsoft Research (original) (raw)
Papers by Titas De
Bone fragility and fracture caused by osteoporosis or injury are prevalent in adults over the age... 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...
We have developed a system for automatic facial expression recognition, which runs on Google Glas... 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.
In recent years, much focus has been put on employing technology to make novel behavioural aids f... 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...
Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, 2016
Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems, 2016
Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2013
Journal of the American Academy of Child & Adolescent Psychiatry
Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct - UbiComp '16, 2016
CHI Workshop - Autism & Technology, 2016
In recent years, much focus has been put on employing technology to make novel behavioral aids fo... more In recent years, much focus has been put on employing technology to make novel behavioral aids for those with autism. Most of these are digital adaptations of tools used in standard behavioral 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, tailored to their specific needs.
Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, 2016
We have developed a system for automatic facial expression recognition, which runs on Google Glas... 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.
US Patent 20160331248A1, 2016
Systems for monitoring blood loss include a display for simultaneously depicting a current blood ... 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.
US Patent 9824441B2, 2017
A system and method for assessing the concentration of a fluid component within a container, th... 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.
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2017
We have developed a system for automatic facial expression recognition running on Google Glass, d... 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.
RSNA, 2014
Osteoporosis is characterized by changes to the trabecular bone micro-architecture in addition to... 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).
Journal of the American Academy of Child and Adolescent Psychiatry, 2017
Applied behavioral analysis (ABA) is an effective form of therapy for children with autism spectr... more Applied behavioral analysis (ABA) is an effective form of therapy for children with autism spectrum disorder (ASD), but it faces criticism for being un-generalizable, too time intensive, and too dependent on specialists to deliver treatment. Earlier age at onset of therapy is one of the strongest predictors of later success, but waitlists to begin therapies can be as long as 18 months. To combat complications associated with the clinical setting and expedite access to therapy, we have begun development of Autism Glass, a machine-learning-assisted software system that runs on Google Glass and an Android Smartphone; it is designed for use in the child’s natural environment during social interactions.This is an exploratory- and co-designed-based study to see how children with ASD respond to our device and examine preliminary data on its effectiveness.
Proceedings of SPIE - Medical Imaging, 2014
The ability of Anisotropic Minkowski Functionals (AMFs) to capture local anisotropy while evaluat... 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.
Proceedings of SPIE - Medical Imaging, 2013
The ability of Minkowski Functionals to characterize local structure in different biological tiss... 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.
Bone fragility and fracture caused by osteoporosis or injury are prevalent in adults over the age... 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...
We have developed a system for automatic facial expression recognition, which runs on Google Glas... 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.
In recent years, much focus has been put on employing technology to make novel behavioural aids f... 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...
Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, 2016
Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems, 2016
Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2013
Journal of the American Academy of Child & Adolescent Psychiatry
Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct - UbiComp '16, 2016
CHI Workshop - Autism & Technology, 2016
In recent years, much focus has been put on employing technology to make novel behavioral aids fo... more In recent years, much focus has been put on employing technology to make novel behavioral aids for those with autism. Most of these are digital adaptations of tools used in standard behavioral 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, tailored to their specific needs.
Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, 2016
We have developed a system for automatic facial expression recognition, which runs on Google Glas... 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.
US Patent 20160331248A1, 2016
Systems for monitoring blood loss include a display for simultaneously depicting a current blood ... 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.
US Patent 9824441B2, 2017
A system and method for assessing the concentration of a fluid component within a container, th... 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.
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2017
We have developed a system for automatic facial expression recognition running on Google Glass, d... 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.
RSNA, 2014
Osteoporosis is characterized by changes to the trabecular bone micro-architecture in addition to... 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).
Journal of the American Academy of Child and Adolescent Psychiatry, 2017
Applied behavioral analysis (ABA) is an effective form of therapy for children with autism spectr... more Applied behavioral analysis (ABA) is an effective form of therapy for children with autism spectrum disorder (ASD), but it faces criticism for being un-generalizable, too time intensive, and too dependent on specialists to deliver treatment. Earlier age at onset of therapy is one of the strongest predictors of later success, but waitlists to begin therapies can be as long as 18 months. To combat complications associated with the clinical setting and expedite access to therapy, we have begun development of Autism Glass, a machine-learning-assisted software system that runs on Google Glass and an Android Smartphone; it is designed for use in the child’s natural environment during social interactions.This is an exploratory- and co-designed-based study to see how children with ASD respond to our device and examine preliminary data on its effectiveness.
Proceedings of SPIE - Medical Imaging, 2014
The ability of Anisotropic Minkowski Functionals (AMFs) to capture local anisotropy while evaluat... 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.
Proceedings of SPIE - Medical Imaging, 2013
The ability of Minkowski Functionals to characterize local structure in different biological tiss... 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.