arXiv subjects

Deepak Bhatia

Publications and source records attributed to Deepak Bhatia.

4 recordsLinked to original sources

arXiv2026

Female-RHINO: A Real-Time Scanner-Integrated Framework for Automated Quantitative Uterine MRI Analysis and Structured Reporting

Standardized assessment of uterine MRI remains challenging due to anatomical variability, observer dependence, and the lack of workflow-integrated automated analysis tools. This work presents Female-RHINO: (R)eproductive (H)ealth (I)maging A(N)alysis T(O)ol, a real-time AI-assisted framework for automated quantitative uterine MRI analysis and structured reporting during image acquisition. We present an end-to-end system that integrates inline communication with the MRI scanner and deep learning-based analysis to derive quantitative uterine biomarkers from sagittal T2-weighted pelvic MRI. The framework combines segmentation and anatomical landmark detection models trained and evaluated on more than 500 multi-center datasets spanning diverse protocols, vendors, and patient populations. It performs volumetry, detects and quantifies common incidental findings such as fibroids and Nabothian cysts, and extracts six anatomical landmarks for biometric assessment. Results are compiled into a structured clinician-oriented report with integrated visualizations, without manual interaction. Evaluation on independent retrospective and prospective cohorts demonstrated robust performance across varying acquisition settings. Mean Dice similarity coefficients were 0.82 for the uterus and 0.80 for fibroids, with lower but consistent agreement for Nabothian cysts. Landmark detection achieved a mean radial error of 3.7 mm. End-to-end processing was completed in under 70 seconds, enabling availability of results during the ongoing scan. Prospective deployment yielded immediate, standardized, and reproducible analyses supported by inter-observer agreement. The proposed system enables real-time scanner-integrated AI for automated uterine MRI analysis and reporting, with potential to improve standardization, efficiency, and clinical workflow in pelvic imaging.

eess.IV↗

arXiv2024

Calculation of Femur Caput Collum Diaphyseal angle for X-Rays images using Semantic Segmentation

This paper investigates the use of deep learning approaches to estimate the femur caput-collum-diaphyseal (CCD) angle from X-ray images. The CCD angle is an important measurement in the diagnosis of hip problems, and correct prediction can help in the planning of surgical procedures. Manual measurement of this angle, on the other hand, can be time-intensive and vulnerable to inter-observer variability. In this paper, we present a deep-learning algorithm that can reliably estimate the femur CCD angle from X-ray images. To train and test the performance of our model, we employed an X-ray image dataset with associated femur CCD angle measurements. Furthermore, we built a prototype to display the resulting predictions and to allow the user to interact with the predictions. As this is happening in a sterile setting during surgery, we expanded our interface to the possibility of being used only by voice commands. Our results show that our deep learning model predicts the femur CCD angle on X-ray images with great accuracy, with a mean absolute error of 4.3 degrees on the left femur and 4.9 degrees on the right femur on the test dataset. Our results suggest that deep learning has the potential to give a more efficient and accurate technique for predicting the femur CCD angle, which might have substantial therapeutic implications for the diagnosis and management of hip problems.

eess.IV↗

arXiv2016

A novel ZnO piezoelectric microcantilever energy scavenger: Fabrication and characterization

This novel piezoelectric zinc oxide (ZnO) thin film microcantilever was fabricated by micromachining technique. To release the cantilever, wet anisotropic etching of Silicon (Si) was performed by tetramethyl ammonium hydroxide (TMAH). The transverse piezoelectric coefficient d31 of the ZnO film, obtained from the deflection of the cantilever with influence of applied voltage, was calculated as 3.32 pC/N. The observed dynamic characterization of the novel piezoelectric microcantilever had linear response with the applied driving voltage. The obtained values of Young Modulus and Hardness were 208 +4 GPa and 4.84+ 0.1 GPa respectively. This inexpensive novel method provides additional design flexibility to fabricate vibrational energy harvesters. The easy steps of fabrication and cost effectiveness of this method may be preferred it over DRIE. The voltage induced due to deformation of ZnO cantilever were measured ~230mV. This microcantilever energy scavenger may be used to power the nano devices and sensors for medical and agricultural applications as a replacement of traditional bulky batteries.

cond-mat.mes-hall↗

arXiv2015

Investigation of Magnetic Domain Structure in Bi0.7Dy0.3FeO3 thin films integrated with ZnO film

The magnetic domain structure of the multiferroic Bi1-xDyxFeO3 (BDFO) deposited on ZnO at the macroscopic level has been demonstrated in this paper. Magnetic properties are observed by saturated magnetic and ferroelectric hysteresis loops at room temperature. The coupling behaviour and magnetic transition are verified using Multimode Atomic Force Microscope by applying bias between sample and MFM tip. ZnO thin film of 300 nm was deposited by dielectric sputtering using a ZnO target on Si p-type conducting (.0001-0005 Ω cm) substrate. BDFO thin films of 300 nm were deposited on Si/ZnO using PLD (Pulsed laser deposition) technique. It is observed that BDFO thin films integrated with ZnO film shows the coexistence of ferromagnetic and ferroelectric ordering with significant coupling at room temperature. Integration of BDFO films with ZnO piezoelectric thin film shows the potential in MEMS applications as well as in Memory devices and strong history dependent systems.

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