arXiv subjects

Azeem Ahmad

Publications and source records attributed to Azeem Ahmad.

At least 19 recordsLinked to original sources

arXiv2026

Motion-guided sparse correction enables expert-quality point tracking across diverse microscopy regimes

Tracking the dynamics of non-canonical biological systems in microscopy videos remains a persistent challenge. Both classical and learning-based trackers depend on expert-reviewed data to be evaluated and adapted, yet exhaustive manual annotation rarely scales to the videos where these tools are needed most. We developed RIPPLE (Refinement Interpolation Platform for Point Location Estimation), which recasts annotation as sparse correction: a user clicks a starting point, RIPPLE proposes a full trajectory, and the user intervenes only where the trajectory drifts. We tested RIPPLE on five challenging microscopy datasets from our laboratories, four from the transparent jellyfish Clytia hemisphaerica and one tracking landmarks on rapidly moving sperm. Across these, RIPPLE matched the quality of exhaustive manual annotation while reducing manual clicks by 3 to 25 times across datasets. RIPPLE thereby fills a missing layer between manual annotation and fully automated tracking, enabling immediate quantification of biological dynamics, method benchmarking, and the production of the gold-standard data needed to adapt future automated microscopy trackers.

cs.CV↗

arXiv2026

Lateral shearing optical diffraction tomography of brain organoid with reduced spatial coherence

Optical diffraction tomography (ODT) is a powerful technique for quantitative, label-free reconstruction of the three-dimensional refractive index (RI) distribution of biological samples. While ODT is well established for imaging thin, weakly scattering samples, it encounters significant challenges when applied to heterogeneous, strongly scattering thick samples such as tissues and organoids. In this work, a novel common-path interferometric approach to ODT is presented, specifically designed for the RI reconstruction of heterogeneous and highly scattering samples at high temporal stability. The proposed technique, termed lateral shearing (LS)-ODT, incorporates partial lateral shearing off-axis interferometry to suppress the effects of multiple scattering, similar to the mechanism in differential interference contrast (DIC) microscopy, which is widely used for imaging thick specimens. Additionally, the LS-ODT system uses dynamic speckle illumination to enhance both spatial phase and RI sensitivity compared to laser-based ODT systems. The effectiveness of this method is demonstrated through experiments on a cell phantom. Its robustness and accuracy are further validated across a wide range of samples, including mouse kidney tissue sections and brain organoids derived from human induced pluripotent stem cells (iPSCs), in both thin and thick sections. Furthermore, correlative fluorescence and RI tomography of the organoids highlights the potential of LS-ODT to enhance and support a broad spectrum of biomedical studies, particularly in the field of histology.

physics.optics↗

arXiv2026

High-Sensitivity, High-Throughput Double Sagnac Lateral Shearing Quantitative Phase Microscopy and Tomography with Pseudo-Thermal Illumination

Quantitative phase microscopy (QPM) enables label-free measurement of local optical path length variations, providing critical insight into the structure and dynamics of transparent biological specimens. Here, a highly sensitive lateral shearing QPM (LS-QPM) system is presented, based on a novel double Sagnac common-path interferometric configuration combined with pseudo-thermal illumination. The pseudo-thermal light source plays a central role in enhancing spatial phase sensitivity by suppressing coherent noise and speckle artifacts, while maintaining sufficient temporal coherence to generate high-density interference fringes, thereby enabling robust single-shot phase retrieval. In addition, the double Sagnac architecture introduces an inherently stable common-path geometry, significantly enhancing temporal phase stability. Unlike conventional quadriwave lateral shearing interferometry (QWLSI)-based QPM systems, which typically suffer from a trade-off between spatial resolution and field of view (FOV), the proposed approach enables simultaneous achievement of diffraction-limited resolution and a large FOV. Experimental validation using calibrated polystyrene beads demonstrates accurate and spatially uniform phase reconstruction across the entire imaging area. Further, the system's capability for biological imaging is demonstrated through experiments on fixed and live HeLa cells, where subcellular features and dynamic processes are captured in a label-free manner. Furthermore, volumetric imaging of embedded bead samples highlights the potential of the approach for three-dimensional phase tomography. The lateral shearing mechanism, analogous to differential interference contrast (DIC), improves robustness to multiple scattering, indicating strong potential for future applications in imaging thick and heterogeneous samples.

physics.optics↗

arXiv2026

High-Fidelity Single-Shot Quantitative Differential Phase Microscopy Using Pseudothermal Sagnac Interferometer

In this letter, a high-fidelity single-shot differential quantitative phase microscopy (dQPM) method is presented to effectively image nearly transparent biological samples. The proposed method is based on a common-path Sagnac interferometric configuration, which provides superior temporal phase stability and robustness against environmental disturbances. The proposed system exploits a pseudothermal source to achieve high spatial sensitivity and generate dense interference fringes for effective single-shot differential quantitative phase imaging. The effectiveness of the proposed system is experimentally demonstrated with various samples, including polystyrene microspheres, a USAF phase target, fixed and live HeLa cells, and mouse kidney tissue.

physics.optics↗

arXiv2026

Differentiable Microscopy Designs an All Optical Phase Retrieval Microscope

Designing new optical systems from the ground up for microscopy imaging tasks such as phase retrieval, requires substantial scientific expertise and creativity. To augment the traditional design process, we propose differentiable microscopy ($\partialμ$), which introduces a top-down design approach. Using all optical phase retrieval as an illustrative example, we demonstrate the effectiveness of data-driven microscopy design through $\partialμ$. Furthermore, we conduct comprehensive comparisons with existing all-optical phase retrieval methods, showcasing the consistent superiority of our learned designs across multiple datasets, including biological samples. To substantiate our ideas, we experimentally validate the functionality of one of the learned designs, providing a proof of concept. The proposed differentiable microscopy framework supplements the creative process of designing new phase microscopy systems and may be extended to other similar applications in optical design.

physics.optics↗

arXiv2025

Bayesian inference for precise and uncertainty-quantified single-shot widefield interferometric geometrical nanometrology

Advanced geometrical nanometrology is critical for process control in semiconductor manufacturing, supporting applications in, e.g., photonic integrated circuits, nanoelectronics, and emerging quantum and optoelectronic technologies. Widefield interferometric approach provide a cost-effective, non-destructive solution for characterizing semiconductor optical waveguides, which are fundamental to nanophotonic devices. This work presents a Bayesian inference framework, implemented using Dynamic Nested Sampling, for estimating geometric parameters - such as width and height - of a semiconductor optical waveguide from a single widefield interferogram. The proposed framework reduces the need of leveraging near field scanning microscopy methods for measurements. The notable advantage is that Bayesian statistics not only provide the estimated parameter values but also quantify the uncertainty of the inference results and the fitness of the used model. The proposed full-field, single-shot interferometric approach, supported by Bayesian-based data analysis, achieves high accuracy and sensitivity - down to successful measurement of 8 nm rib waveguide - while remaining resilient to noise. Thus, the demonstrated methodology provides a cost-effective, robust, and scalable tool for semiconductor fabrication monitoring and process verification, as confirmed by both numerical simulations and experimental validation on optical waveguides. This method contributes to high-precision nanometrology by integrating advanced statistical modeling and inference techniques.

physics.optics↗

arXiv2024

Gradient Optical Diffraction Tomography

Optical diffraction tomography (ODT) enables non-invasive information-rich 3D refractive index (RI) reconstruction of unimpaired transparent biological and technical samples, crucial in biomedical research, optical metrology, materials sciences, and other fields. ODT bypasses the inherent limitations of 2D integrated quantitative phase imaging methods. To increase the signal-to-noise ratio easy-to-implement common-path shearing interferometry setups are successfully combined with low spatiotemporal coherence of illumination. The need for self-interference generated holograms, with small shear values, critically impedes the analysis of dense and thick samples, e.g., cell cultures, tissue sections, and embryos/organoids. Phase gradient imaging techniques, deployed as a popular solution in the small shear regime, up to now were constrained to 2D integrated quasi-quantitative phase imaging and z-scanning for depth resolution. To fill this significant scientific gap, we propose a novel gradient optical diffraction tomography (GODT) method. The GODT uses coherence-tailored illumination-scanning sequence of phase gradient measurements to tomographically reconstruct, for the first time to the best of our knowledge, a derivative of the 3D RI distribution (in the shear direction) with clearly visible 3D sample structure and high sensitivity to its spatial variations. We present a mathematically rigorous theory based on the first-order Rytov approximation behind the new method, validate it using simulations deploying numerical Shepp-Logan target and corroborate experimentally via successful tomographic imaging of the calibrated nano-printed cell phantom and efficient examination of neural cells. This novel imaging modality opens new possibilities in biomedical quantitative phase imaging, advancing the field and putting forward a first of a kind contrast domain: 3D RI gradient.

physics.optics↗

arXiv2023

From Hours to Seconds: Towards 100x Faster Quantitative Phase Imaging via Differentiable Microscopy

With applications ranging from metabolomics to histopathology, quantitative phase microscopy (QPM) is a powerful label-free imaging modality. Despite significant advances in fast multiplexed imaging sensors and deep-learning-based inverse solvers, the throughput of QPM is currently limited by the speed of electronic hardware. Complementarily, to improve throughput further, here we propose to acquire images in a compressed form such that more information can be transferred beyond the existing electronic hardware bottleneck. To this end, we present a learnable optical compression-decompression framework that learns content-specific features. The proposed differentiable quantitative phase microscopy ($\partial μ$) first uses learnable optical feature extractors as image compressors. The intensity representation produced by these networks is then captured by the imaging sensor. Finally, a reconstruction network running on electronic hardware decompresses the QPM images. In numerical experiments, the proposed system achieves compression of $\times$ 64 while maintaining the SSIM of $\sim 0.90$ and PSNR of $\sim 30$ dB on cells. The results demonstrated by our experiments open up a new pathway for achieving end-to-end optimized (i.e., optics and electronic) compact QPM systems that may provide unprecedented throughput improvements.

eess.IV↗

arXiv2022

Hilbert phase microscopy based on pseudo thermal illumination in Linnik configuration

Quantitative phase microscopy (QPM) is often based on recording an object-reference interference pattern and its further phase demodulation. We propose Pseudo Hilbert Phase Microscopy (PHPM) where we combine pseudo thermal light source illumination and Hilbert spiral transform phase demodulation to achieve hybrid hardware-software-driven noise robustness and increase in resolution of single-shot coherent QPM. Those advantageous features stem from physically altering the laser spatial coherence and numerically restoring spectrally overlapped object spatial frequencies. Capabilities of the PHPM are demonstrated analyzing calibrated phase targets and live HeLa cells in comparison with laser illumination and phase demodulation via temporal phase shifting and Fourier transform techniques. Performed studies verified unique ability of the PHPM to couple single-shot imaging, noise minimization, and preservation of phase details.

physics.optics↗

arXiv2022

Transmission Structured Illumination Microscopy using Tilt-mirror Assembly

We present experimental demonstration of tilt-mirror assisted transmission structured illumination microscopy (tSIM) that offers a large field of view super resolution imaging. An assembly of custom-designed tilt-mirrors are employed as the illumination module where the sample is excited with the interference of two beams reflected from the opposite pair of mirror facets. Tunable frequency structured patterns are generated by changing the mirror-tilt angle and the hexagonal-symmetric arrangement is considered for the isotropic resolution in three orientations. Utilizing high numerical aperture (NA) objective in standard SIM provides super-resolution compromising with the field-of-view (FOV). Employing low NA (20X/0.4) objective lens detection, we experimentally demonstrate ~ (0.56mm x 0.35mm) size single FOV image with ~1.7- and ~2.4-fold resolution improvement (exploiting various illumination by tuning tilt-mirrors) over the diffraction limit. The results are verified both for the fluorescent beads as well as biological samples. The tSIM geometry decouples the illumination and the collection light paths consequently enabling free change of the imaging objective lens without influencing the spatial frequency of the illumination pattern that are defined by the tilt-mirrors. The large and scalable FoV supported by tSIM will find usage for applications where scanning large areas are necessary as in pathology and applications where images must be correlated both in space and time.

physics.optics↗

arXiv2022

Image denoising in acoustic field microscopy

Scanning acoustic microscopy (SAM) has been employed since microscopic images are widely used for biomedical or materials research. Acoustic imaging is an important and well-established method used in nondestructive testing (NDT), bio-medical imaging, and structural health monitoring.The imaging is frequently carried out with signals of low amplitude, which might result in leading that are noisy and lacking in details of image information. In this work, we attempted to analyze SAM images acquired from low amplitude signals and employed a block matching filter over time domain signals to obtain a denoised image. We have compared the images with conventional filters applied over time domain signals, such as the gaussian filter, median filter, wiener filter, and total variation filter. The noted outcomes are shown in this article.

eess.IV↗

arXiv2022

Multiple damage detection in piezoelectric ceramic sensor using point contact excitation and detection method

Lead Zirconate Titanate [(ZrxTi1-x)O3 ]is used to make ultrasound transducers, sensors, and actuators due to its large piezoelectric coefficient. Several surfaces and subsurface micro defects develop within the Lead Zirconate Titanate (PZT) sensor due to delamination, corrosion, huge temperature fluctuation, etc., causing a decline in its performance. It is thus necessary to identify, locate, and quantify the defects. Non-Destructive Structural Health Monitoring (SHM) is the most optimal and economical method of evaluation. Traditional ultrasound SHM techniques have a huge impedance mismatch between air and any solid material. And most of the popular signal processing methods define time-series signals in only one domain which gives sub-optimal results. Thus to improve the accuracy of detection point contact excitation and detection methods have been implemented to determine the interaction of ultrasonic waves with microscale defects in the PZT. And Haar Discrete Wavelet Transformation (DWT) is applied to the time series data obtained from the Coulomb coupling setup. Using the above process, defect up to 100 um in diameter could be successfully distinguished and localized.

physics.app-ph↗

arXiv2022

Surface acoustic waves inside polystyrene microparticles through photoacoustic microscopy

We demonstrate surface acoustic waves inside polystyrene microspheres of different sizes experimentally through photoacoustic microscopy and validate the experimental result with simulation. A novel method for sample preparation of a lifted sample is also presented where the microparticles are suspended in agarose above the surface of the petridish. Another objective of this study was to investigate the results with different laser focus hitting on the microparticles and their impact on photoacoustic images and photoacoustic signals. An absorbing microsphere is excited with a pulsed laser of wavelength 532 nm and the photoacoustic signal is detected using a 40 MHz transducer. On analyzing the photoacoustic signals from microspheres, we find the signature of surface acoustic waves.

physics.class-ph↗

arXiv2021

Demystifying speckle field quantitative phase microscopy

Quantitative phase microscopy (QPM) has found significant applications in the field of biomedical imaging which works on the principle of interferometry. The theory behind achieving interference in QPM with conventional light sources such as white light and lasers is very well developed. Recently, the use of dynamic speckle illumination (DSI) in QPM has attracted attention due to its advantages over conventional light sources such as high spatial phase sensitivity, single shot, scalable field of view (FOV) and resolution. However, the understanding behind obtaining interference fringes in QPM with DSI has not been convincingly covered previously. This imposes a constraint on obtaining interference fringes in QPM using DSI and limits its widespread penetration in the field of biomedical imaging. The present article provides the basic understanding of DSI through both simulation and experiments that is essential to build interference optical microscopy systems such as QPM, digital holographic microscopy and optical coherence tomography. Using the developed theory of DSI we demonstrate its capabilities of using non-identical objective lenses in both arms of the interference microscopy without degrading the interference fringe contrast and providing the flexibility to use user-defined microscope objective lens. It is also demonstrated that the interference fringes are not washed out over a large range of optical path difference (OPD) between the object and the reference arm providing competitive edge over low temporal coherence light sources. The theory and explanation developed here would enable wider penetration of DSI based QPM for applications in biology and material sciences.

physics.optics↗

arXiv2020

High throughput spatially sensitive single-shot quantitative phase microscopy

High space-bandwidth product with high spatial phase sensitivity is indispensable for a single-shot quantitative phase microscopy (QPM) system. It opens avenue for widespread applications of QPM in the field of biomedical imaging. Temporally low coherence length light sources are generally implemented to achieve high spatial phase sensitivity in QPM at the cost of either reduced temporal resolution or smaller field of view (FOV). On the contrary, high temporal coherence light sources like lasers are capable of exploiting the full FOV of the QPM systems at the expense of less spatial phase sensitivity. In the present work, we employed pseudo-thermal light source (PTLS) in QPM which overcomes the limitations of conventional light sources. The capabilities of PTLS over conventional light sources are systematically studied and demonstrated on various test objects like USAF resolution chart and thin optical waveguide (height ~ 8 nm). The spatial phase sensitivity of QPM in case of PTLS is measured to be equivalent to that for white light source. The high-speed and large FOV capabilities of PTLS based QPM is demonstrated by high-speed imaging of live sperm cells that is limited by the camera speed and by imaging extra-ordinary large FOV phase imaging on histopathology placenta tissue samples.

physics.optics↗

arXiv2020

Multi-modal on-chip nanoscopy and quantitative phase image reveals the morphology of liver sinusoidal enodthelial cells

Visualization of three-dimensional morphological changes in the subcellular structures of a biological specimen is one of the greatest challenges in life science. Despite conspicuous refinements in optical nanoscopy, determination of quantitative changes in subcellular structure, i.e., size and thickness, remains elusive. We present an integrated chip-based optical nanoscopy set-up that provides a lateral optical resolution of 61 nm combined with a highly sensitive quantitative phase microscopy (QPM) system with a spatial phase sensitivity of $\pm$20 mrad. We use the system to obtain the 3D morphology of liver sinusoidal endothelial cells (LSECs) combined with super-resolved spatial information. LSECs have a unique morphology with nanopores that are present in the plasma membrane, called fenestration. The fenestrations are grouped in clusters called sieve plates, which are around 100 nm thick. Thus, imaging and quantification of fenestration and sieve plate thickness requires resolution and sensitivity of sub-100 nm along both lateral and axial directions. In the chip-based nanoscope, the optical waveguides are used both for hosting and illuminating the sample. A strong evanescent field is generated on top of the waveguide surface for single molecule fluorescence excitation. The fluorescence signal is captured by an upright microscope, which is converted into a Linnik-type interferometer to sequentially acquire both super-resolved images and quantitative phase information of the sample. The multi-modal microscope provided an estimate of the fenestration diameter of 124$\pm$41 nm and revealed the average estimated thickness of the sieve plates in the range of 91.2$\pm$43.5 nm for two different cells. The combination of these techniques offers visualization of both the lateral size (using nanoscopy) and the thickness map of sieve plates, i.e. discrete clusters fenestrations in QPM mode.

physics.bio-ph↗

arXiv2020

Deep learning architecture LightOCT for diagnostic decision support using optical coherence tomography images of biological samples

Optical coherence tomography (OCT) is being increasingly adopted as a label-free and non-invasive technique for biomedical applications such as cancer and ocular disease diagnosis. Diagnostic information for these tissues is manifest in textural and geometric features of the OCT images, which are used by human expertise to interpret and triage. However, it suffers delays due to the long process of the conventional diagnostic procedure and shortage of human expertise. Here, a custom deep learning architecture, LightOCT, is proposed for the classification of OCT images into diagnostically relevant classes. LightOCT is a convolutional neural network with only two convolutional layers and a fully connected layer, but it is shown to provide excellent training and test results for diverse OCT image datasets. We show that LightOCT provides 98.9% accuracy in classifying 44 normal and 44 malignant (invasive ductal carcinoma) breast tissue volumetric OCT images. Also, >96% accuracy in classifying public datasets of ocular OCT images as normal, age-related macular degeneration and diabetic macular edema. Additionally, we show ~96% test accuracy for classifying retinal images as belonging to choroidal neovascularization, diabetic macular edema, drusen, and normal samples on a large public dataset of more than 100,000 images. The performance of the architecture is compared with transfer learning based deep neural networks. Through this, we show that LightOCT can provide significant diagnostic support for a variety of OCT images with sufficient training and minimal hyper-parameter tuning. The trained LightOCT networks for the three-classification problem will be released online to support transfer learning on other datasets.

physics.med-ph↗

arXiv2020

High space-bandwidth in quantitative phase imaging using partially spatially coherent optical coherence microscopy and deep neural network

Quantitative phase microscopy (QPM) is a label-free technique that enables to monitor morphological changes at subcellular level. The performance of the QPM system in terms of spatial sensitivity and resolution depends on the coherence properties of the light source and the numerical aperture (NA) of objective lenses. Here, we propose high space-bandwidth QPM using partially spatially coherent optical coherence microscopy (PSC-OCM) assisted with deep neural network. The PSC source synthesized to improve the spatial sensitivity of the reconstructed phase map from the interferometric images. Further, compatible generative adversarial network (GAN) is used and trained with paired low-resolution (LR) and high-resolution (HR) datasets acquired from PSC-OCM system. The training of the network is performed on two different types of samples i.e. mostly homogenous human red blood cells (RBC) and on highly heterogenous macrophages. The performance is evaluated by predicting the HR images from the datasets captured with low NA lens and compared with the actual HR phase images. An improvement of 9 times in space-bandwidth product is demonstrated for both RBC and macrophages datasets. We believe that the PSC-OCM+GAN approach would be applicable in single-shot label free tissue imaging, disease classification and other high-resolution tomography applications by utilizing the longitudinal spatial coherence properties of the light source.

physics.bio-ph↗