Uncooled IR polarimetric imaging camera and performance metrics (Conference Presentation)

The emergence of fully volumetric CT imaging systems and statistical / iterative reconstruction methods present an immediate need for rigorous methods of image quality assessment. Major themes arising in the widespread utilization of such technologies include: 1.) the reduction of radiation dose in a manner that maintains imaging performance with respect to the imaging task; 2.) the need for quantitative standards in image quality assessment appropriate to various vendor hardware and reconstruction systems; 3.) imaging performance metrics that provide meaningful descriptors of fully 3D spatial resolution and noise characteristics; 4.) the dependence of these metrics on acquisition technique, reconstruction parameters, and their applicability (or lack thereof) to novel reconstruction methods that may defy conventional metrics founded in assumptions of linearity and shift invariance; and 5.) methods for physical measurement (e.g., phantoms) and theoretical analysis of image quality for these new and emerging CT technologies and their implications for dose reduction.Learning Objectives:1. Understand the methods and metrics of image quality assessment for fully volumetric (cone‐beam) CT imaging using 3D filtered backprojection, including analysis of the 3D NPS, NEQ, and detectability index.2. Understand the limitations and assumptions of such metrics with respect to linearity, stationarity, and novel reconstruction techniques.3. Gain an understanding of how rigorous assessment of imaging performance can guide technique optimization, dose reduction, and the development of new CT technologies and applications.4. Understand the factors of image quality assessment in nonlinear statistical / model‐based 3D reconstruction techniques, including PSF and covariance estimation in nonstationary systems.5. Gain perspective on image quality assessment standards, including methods for dose and image quality measurement on different vendor platforms and the implications for dose reduction.

Mounting evidence suggests that the superposition of anatomical clutter in a projection radiograph poses a major impediment to the detectability of subtle lung nodules. Through decomposition of projections acquired at multiple kVp, dual-energy (DE) imaging offers to dramatically improve lung nodule detectability and, in part through quantitation of nodule calcification, increase specificity in nodule characterization. The development of a high-performance DE chest imaging system is reported, with design and implementation guided by fundamental imaging performance metrics. A diagnostic chest stand (Kodak RVG 5100 digital radiography system) provided the basic platform, modified to include: (i) a filter wheel, (ii) a flat-panel detector (Trixell Pixium 4600), (iii) a computer control and monitoring system for cardiac-gated acquisition, and (iv) DE image decomposition and display. Computational and experimental studies of imaging performance guided optimization of key acquisition technique parameters, including: x-ray filtration, allocation of dose between low- and high-energy projections, and kVp selection. A system for cardiac-gated acquisition was developed, directing x-ray exposures to within the quiescent period of the heart cycle, thereby minimizing anatomical misregistration. A research protocol including 200 patients imaged following lung nodule biopsy is underway, allowing preclinical evaluation of DE imaging performance relative to conventional radiography and low-dose CT.

The optical detection of surface capillary-gravity waves induced by underwater sound has many potential applications that range from the detection of sound-generating underwater objects to airborne bathymetric surveys. While multiple lab-based efforts have measured acoustically generated surface capillary-gravity waves, we report on a recent field-based measurement using polarimetric imaging. A controlled acoustic source was placed 10 m below a lake surface and emitted sound in the 500 Hz to 10000Hz frequency range. The lake surface was imaged using a polarimetric camera mounted 7 m above the lake surface. Measurable short-lived surface capillary-gravity waves (∼3 mm wavelength) were observed in the polarimetric camera images during ensonification of the lake surface. Changes were observed in both the omnidirectional and directional wave spectra. In the omni-directional wavenumber spectrum, enhanced capillary wave activity at high wavenumbers was observed for acoustic source frequencies in the 2–5 kHz range. Additionally, ensonification was observed to result in the amplitude and wavenumber modulation (enhancement/diminution) of existing wind-generated surface gravity-capillary waves. In the directional spectra, while ambient gravity-capillary waves showed a spreading function with stronger downwind versus upwind propagation, the acoustically generated gravity-capillary waves showed minimal impact on the directionality of the wave spectra.

Paper 10002, 9 S.

We compare the measurement precision of a polarimetric camera to that of a simple intensity camera when imaging a partially polarized light-mark embedded in an intense and partially polarized background. We show that the gain in measurement precision while using a polarimetric camera is maximized when the noise fluctuations on the two polarimetric channels are significantly correlated. Further, we implement a snapshot polarimetric camera for long distance imaging of a highly polarized light source through fog and compare the contrast obtained using various representations of the polarimetric images. We show that the representation that provides the best contrast depends on the visibility conditions and matches well with theoretical predictions.

Towards real-time polarimetric de-scattering imaging: From thread framework to algorithm optimization and underwater demonstration

We propose a polarimetric microwave imaging technique that exploits recent advances in computational imaging. We utilize a frequency-diverse cavity-backed metasurface, allowing us to demonstrate high-resolution polarimetric imaging using a single transceiver and frequency sweep over the operational microwave bandwidth. The frequency-diverse metasurface imager greatly simplifies the system architecture compared with active arrays and other conventional microwave imaging approaches. We further develop the theoretical framework for computational polarimetric imaging and validate the approach experimentally using a multi-modal leaky cavity. The scalar approximation for the interaction between the radiated waves and the target- often applied in microwave computational imaging schemes-is thus extended to retrieve the susceptibility tensors, and hence provides additional information about the targets. Computational polarimetry has relevance for existing systems in the field that extract polarimetric imagery, and particular for ground observation. A growing number of short-range microwave imaging applications can also notably benefit from computational polarimetry, particularly for imaging objects that are difficult to reconstruct when assuming scalar estimations.

This scoping review aimed to answer the question: to what extent do artificial intelligence applications in dental and orthopedic skeletal imaging demonstrate true cross-disciplinary methodological convergence versus parallel development with shared translational barriers? This scoping review synthesizes AI applications across both fields to characterize methodological overlap, developmental asymmetries, and translational gaps, rather than assuming convergence. Following the PRISMA-ScR reporting standards, we searched PubMed, Scopus, Web of Science, IEEE Xplore, and EMBASE for peer-reviewed, English-language human studies published between January 2015 and May 2025. Eligible studies applied AI, machine learning, or deep learning to diagnostic, segmentation, or preoperative planning tasks in dental or orthopedic imaging. Three reviewers independently extracted data on imaging modality, task, model architecture, dataset characteristics, validation strategy, performance metrics, and translational considerations, with random auditing for consistency. Fifty-nine studies met inclusion criteria, comprising 48 dental (81.36%) and 11 orthopedic (18.64%) investigations, with no study spanning both domains. Most applications focused on foundational tasks such as segmentation and detection/classification using two-dimensional radiographs and cone-beam computed tomography. Computed tomography primarily supported bony anatomy and preoperative planning, while magnetic resonance imaging, the EOS system, and intraoral scanners were used in specialized workflows. Convolutional neural networks, particularly U-Net/nnU-Net variants and EfficientNet/ResNet backbones with YOLO-based detectors, dominated, alongside emerging transformer-based and hybrid physics-informed approaches. Internal validation performance was frequently high for segmentation (typical Dice 0.90-0.99), while more complex or anatomically challenging targets showed lower and more variable performance. External validation, prospective evaluation, and standardized reporting of calibration, expert comparators, and demographic performance were uncommon. The current AI skeletal imaging literature demonstrates strong technical feasibility but uneven clinical maturity, with dental imaging dominating in volume and automation of foundational tasks and orthopedic applications remaining fewer, more heterogeneous, and less mature. Rather than evidencing true cross-disciplinary convergence, the findings highlight asymmetrical development and shared translational barriers, particularly in validation rigor and real-world integration. By explicitly identifying these asymmetries, this review provides a realistic foundation for future cross-disciplinary collaboration focused on harmonized validation standards, clinically meaningful benchmarks, and equitable, workflow-native deployment.

To improve signal detection in a turbid medium, we propose temporally encoded single shot polarimetric integral imaging. An optical signal is temporally encoded using gold coded sequences and transmitted through a turbid medium. The encoded signals are captured as a sequence of elemental images by two orthogonal polarized image sensor arrays. Polarimetric and polarization difference imaging are used to suppress the partially polarized and unpolarized background noise such that only the polarized ballistic signal photons are captured at the sensor. Multidimensional integral imaging is used to obtain 4D reconstructed data, and multidimensional nonlinear correlation is performed on the reconstructed data to detect the optical signal. We compare the effectiveness of the proposed polarimetric underwater optical signal detection approach to conventional (non-polarimetric) integral imaging-based and 2D imaging-based signal detection systems. The underwater signal detection capabilities are measured through performance metrics such as receiver operating characteristic (ROC) curves, the area under the curve (AUC), and the number of detection errors. Furthermore, statistical measures, including the Kullback-Leibler divergence, signal-to-noise ratio (SNR), and peak-to-correlation energy (PCE), are also calculated to show the improved performance of the proposed system. Our experimental results show that the proposed polarimetric integral-imaging approach significantly outperforms the conventional imaging-based methods. To the best of our knowledge, this is the first report on temporally encoded single shot polarimetric integral imaging for signal detection in turbid water.

Conventional Muller matrix imaging polarimeter (MMIP) with several rotating elements suffers mechanical complexity, vibration noise, heat generation, and other unwanted problems. To overcome those shortcomings, we present a snapshot Muller matrix imaging polarimeter (SMMIP) using a birefringent crystal with high extinction ratio. The snapshot imaging polarimeter allows a single image to be used to measure the polarization of a scene without electronic control units or moving mechanical components. This new polarimeter combines the technique of Muller matrix spectropolarimetry with a snapshot imaging polarimeter through using modified Savart polariscope (MSP-SMMIP). It contains both a generator and an analyzer module. Spatial polarization fringes are localized on a sample by incorporating modified Savart polariscope into a polarization generator module. These fringes modulate the Mueller matrix components of the sample, which are subsequently isolated with modified Savart polariscope in an analyzer module, and the analyzer and the imaging lens combine with 16 beams to create interference, resulting in spatial modulation on the two-dimensional CCD camera. Expressions for interference intensities, optical system analysis, theory of calibration and method of reconstruction are presented. Finally, the numerical simulation is used to demonstrate theoretical analysis and the feasibility of MSP-SMMIP. The layout is very easy to calibrate and the reference target is only a linear polarizer at 22.5°. Moreover, the remarkable advantages of the proposed instrument, compared with conventional Muller matrix imaging polarimeter, are that it is also simple, compact, snapshotted, and static (no moving parts). Therefore we believe that the proposed snapshot imaging polarimeter will be very useful in many applications, such as biomedical imaging and remote sensing.

This paper presents the demonstrator of a fully polarimetric ultra-wideband (UWB) multistatic imaging system for screening of groups of walking people in public areas. The system is working in the FCC UWB frequency band from 3.6 GHz to 10.6 GHz. The low frequency range is chosen to reduce the influence and clutter of clothes to a minimum. This is important for the screening in public places because the scanner needs to identify threats even under thick and heavy jackets with a low false alarm rate. Furthermore, the effect of motion blurring in the reconstructed radar images is enormously reduced. To further improve the detection of threats a fully polarimetric radar frontend was chosen for the imaging system. Radar polarimetry is a well-established technique in remote sensing to characterize di erent scattering mechanisms like single and double bounce or volumetric scattering. This offers the opportunity to classify different terrain properties or manmade objects in remote sensing. The investigated antenna arrangement is a roof-like geometry which can be installed on ceilings or archways in public areas. This approach doesn't disturb the flow of walking persons and even could enable a hidden installation of the screening device. Furthermore, this arrangement reduces shadowing risks, i.e. that a terrorist hides himself between closely walking neighbors. The paper discusses the applied signal processing and the polarimetric evaluation. Results are demonstrated for static and dynamic scenarios.

We report on progress made in developing a polarimetric and multispectral imaging (MSI) camera that uses a coded filter mask to record spectral data on either a single frame or only a few frames depending on the design of the mask and the application. The design uses commercially available variable filters and beamsplitters to record spectral data simultaneously on a focal plane array, thus negating the need for scanning mechanisms or dispersive optical elements. The data rate depends on the design of the filter mask, pixel resolution, relative motion between target and camera, and the frame rate. The polarimetric data is recorded on a single frame thus eliminating latency. Multispectral data may be recorded on a few frames or a single frame, thus reducing the need for many multi-frame acquisitions. An optimum mask design matched to the imaging lens and focal plane array resolution, allows an object to be detected against spectral clutter or background on a single pixel. Thus a spatially resolved image is not required, alleviating the need for high magnification which would be a practical limitation where compact optical systems are required. The proof-of-principle is reported that uses a 1D variable filter mask to provide spectra of resolved target images in the near field for the visible spectrum. Test data are presented that show the potential for the concept and how it is readily extended to use a 2D mask in a modified design.

SPHERE (Spectro-Polarimetric High Contrast Exoplanet Research) is one of the first instruments which aim for the direct detection from extra-solar planets. SPHERE commissioning is foreseen in 2013 on the VLT. ZIMPOL (Zurich Imaging Polarimeter) is the high contrast imaging polarimeter subsystem of the ESO SPHERE instrument. ZIMPOL is dedicated to detect the very faint reflected and hence polarized visible light (600-900 nm) from extrasolar planets. It is located behind an extreme AO system (SAXO) and a stellar coronagraph. We present the first high contrast polarimetric results obtained for the fully integrated SPHERE-ZIMPOL system. We have measured the polarimetric high contrast performance of several coronagraphs: a Classical Lyot on substrate, a suspended Classical Lyot and two 4 Quadrant Phase Mask coronagraphs. We describe the impact of crucial system parameters – Adaptive Optics, Coronagraphy and Polarimetry - on the contrast performance.

Breast cancer remains a major healthcare challenge, highlighting the need for early and accurate diagnosis. Shear-wave elastography (SWE), an ultrasound-based imaging technique that quantifies tissue elasticity, has emerged as a promising tool. Recent studies suggest that SWE may provide additional diagnostic value when used alongside conventional imaging methods. This study aimed to assess the diagnostic performance of SWE when combined with conventional ultrasound and magnetic resonance imaging (MRI) in the evaluation of breast lesions. This retrospective study included patients with breast lesions who underwent SWE, conventional ultrasound and MRI. The diagnostic performance of each modality was evaluated individually and in combination. Histopathological results served as the gold standard for diagnosis. Key performance metrics - sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy - were calculated for each imaging approach. A total of 99 patients were included in the study, comprising 64 with benign lesions and 35 with malignant lesions. Malignant lesions were generally larger and exhibited distinct imaging characteristics across ultrasound, SWE and MRI. When assessed individually, SWE, ultrasound and MRI showed comparable diagnostic accuracy (64.6%, 62.6% and 62.6%, respectively). However, combining all 3 modalities significantly improved diagnostic performance, yielding sensitivity, specificity, PPV, NPV, and overall accuracy of 94.3%, 89.1%, 82.5%, 96.6%, and 90.9%, respectively (p < 0.001). The area under the curve (AUC) for the combined approach was significantly higher than for any single modality (0.917 vs 0.642, 0.627 and 0.633; p < 0.001). While SWE alone offers diagnostic performance comparable to that of ultrasound and MRI individually, its greatest value lies in combination with these imaging modalities. Integrating ultrasound, SWE and MRI significantly enhances diagnostic accuracy, sensitivity and specificity, offering a promising multimodal approach for more reliable differentiation between benign and malignant breast lesions.

In this paper, we have presented an adaptive bandelets based on Bayesshrink soft-thresholding despeckling method for polarimetric SAR images. Experimental results demonstrate that our algorithm has a good despeckling performance in polarimetric SAR images and typically preserves even the minor edges comparing with wavelet transform. Besides, the quantitative analysis of evaluation parameters is not difficult to find that the algorithm proposed in this paper is the optimal speckle reduction.