Counting Pixel Research Articles

Dual-Frequency Lidar for Compressed Sensing 3D Imaging Based on All-Phase Fast Fourier Transform

Lidar, with its advantages of high measurement accuracy, fine angular resolution, and strong anti-interference capability, plays a pivotal role in the field of scene depth information acquisition. Traditional approaches to achieving lateral spatial resolution in imaging include raster scanning and array detectors. The former necessitates frequent scanning to acquire depth maps, resulting in time consumption and instability. The latter encounters challenges such as high dark count rates, pixel crosstalk, and excessive costs for obtaining high-resolution images using array detectors. The introduction of compressed sensing (CS) offers a novel perspective on realizing non-scanning three-dimensional imaging. In this context, we propose a novel three-dimensional imaging system that combines CS with coherent dual-frequency continuous-wave lidar and utilizes the all-phase fast Fourier transform to extract both amplitude and phase information. This system requires only M measurements, and through a reconstruction algorithm, it achieves the inversion of depth information for N-pixel scenes (M << N). Integrating cost-effective components such as digital micromirrors and single-point detectors, this affordable system accomplishes three-dimensional imaging of a single target. Notably, it significantly reduces the required number of measurements while concurrently ensuring enhanced eye safety and signal-to-noise ratio.

Identification of new cold tolerant Zoysia grass species using high-resolution RGB and multi-spectral imaging

Zoysia grass (Zoysia spp.) is the most widely used warm-season turf grass in Korea due to its durability and resistance to environmental stresses. To develop new longer-period greenness cultivars, it is essential to screen germplasm which maintains the greenness at a lower temperature. Conventional methods are time-consuming, laborious, and subjective. Therefore, in this study, we demonstrate an objective and efficient method to screen maintaining longer greenness germplasm using RGB and multispectral images. From August to December, time-series data were acquired and we calculated green cover percentage (GCP), Normalized Difference Vegetation Index (NDVI), Normalized Difference Red Edge Index (NDRE), Soil-adjusted Vegetation Index (SAVI), and Enhanced Vegetation Index (EVI) values of germplasm from RGB and multispectral images by applying vegetation indexs. The result showed significant differences in GCP, NDVI, NDRE, SAVI, and EVI among germplasm (p < 0.05). The GCP, which evaluated the quantity of greenness by counting pixels of the green area from RGB images, exhibited maintenance of greenness over 90% for August and September but, sharply decrease from October. The study found significant differences in GCP and NDVI among germplasm. san208 exhibiting over 90% GCP and high NDVI values during 153 days. In addition, we also conducted assessments using various vegetation indexes, namely NDRE, SAVI, and EVI. san208 exhibited NDRE levels exceeding 3% throughout this period. As for SAVI, it initially started at approximately 38% and gradually decreased to around 4% over the course of these days. Furthermore, for the month of August, it recorded approximately 6%, but experienced a decline from about 9% to 1% between September and October. The complementary use of both indicators could be an efficient method for objectively assessing the greenness of turf both quantitatively and qualitatively.

Background rates in several hard X-ray photon counting pixel array detectors

Background rates in several pixel array detectors are investigated with an eye toward using them with hard, >6 keV, X-rays in very low-rate experiments - e.g., at signal rates <0.1/s/cm2. Measured background event rates for a detector with an unshielded 0.75 mm thick CdTe sensor on the experimental floor at SPring-8 varied from 0.4/s/cm2 with a 6 keV lower-level discriminator (LLD) threshold to 0.2/s/cm2 with a 75 keV LLD threshold. The background for a detector with a 1 mm thick silicon sensor was smaller, ∼0.08/s/cm2 for a 3keV threshold dropping to ∼0.07/s/cm2 at a 17 keV threshold. These rates are dominated by terrestrial sources, such as gamma rays emitted from trace impurities in concrete, with only a small contribution, <0.01/s/cm2, from direct detection of cosmic ray muons (CRMs). 15 mm of Pb shielding reduces the measured rates to < 0.05/s/cm2 in CdTe and to < 0.02/s/cm2 in 1 mm silicon. Additional processing, “time slicing”, as may be used in low-rate experiments where backgrounds may be most problematic, is shown to reduce the background rates further, to < 0.004/s/cm2 with the silicon sensor, and to between 0.002 and 0.02/s/cm2 for CdTe, where the exact value for CdTe depends sensitively on the detector threshold, and the use of the retriggering and/or the use of dual discriminator thresholds. Background rates are presented as functions of discriminator threshold, shielding, and processing. We also discuss the magnitude of, and the correction for, the limitation of the detector dynamic range that can be introduced by the time slicing. Finally, we present one example where time slicing was used.

Charge sharing simulations and measurements for digital algorithms aiming at subpixel resolution in photon counting pixel detectors

Hybrid pixel detectors are segmented devices used for X-ray detection that consist of a sensor attached to the readout electronics. Detectors working in single-photon counting mode process each incoming photon individually, have essentially infinite dynamic range, and by applying energy discrimination they provide noiseless imaging. To improve the resolution of the detector and allow operation with high-intensity photon fluxes, the pixel size is reduced. However, with decreasing pixel size, a charge sharing effect is more prominent. This leads to false event registration or omitting the event, and degradation of the energy resolution of the detector. Algorithms aiming at reducing the influence of charge sharing have already been implemented on-chip. However, the spatial resolution of the detector can be increased beyond the physical size of the pixel if the charge proportions collected by neighboring pixels are analyzed.The simulations show that charge cloud size referred to pixel size and noise are the key parameters that determine the accuracy of the subpixel algorithm. The article shows the concept of subpixel algorithm and the simulations for different detector parameters and approximation algorithms. The slanted-edge method was implemented to quantify the resolution of detectors consisting standard readout architecture. The chips were simulated and tested to verify the influence of different bias voltages, sensor materials, and thicknesses on charge sharing and as a consequence on the detector resolution. The simulated and measured edge spread functions were compared. The results show that the simulator can be used to describe the spatial resolution of the detectors, and can be used for further studies of the resolution of detectors with subpixel algorithm implemented.

Experimental characterization of a fast X-ray spectroscopic imager module using the ALTAIR P3 ASIC for real-time contaminants detection

X-ray imagers with spectroscopic capabilities and high photon count rates are finding promising applications in industrial real-time inspection systems. In this context, XSpectra® combines a CdTe-based linear energy-resolved photon counting (ERPC) pixel sensor with real-time image processing techniques to detect low and high density contaminants. The detection unit makes use of a new analog read-out ASIC that has been designed by Politecnico di Milano to meet strict application requirements both in energy resolution and achievable photon count rate. A room-temperature low-rate spectroscopic characterization of the system at a peaking time of 60 ns showed an average equivalent noise charge of 259 electrons r.m.s. (2.72 keV FWHM in CdTe) and an average FWHM of the 59.5 keV 241Am line of 3.6 keV, with a 3σ dispersion in noise performance of ±10% over 256 channels. The detection unit was tested in high incoming photon flux conditions by means of an X-ray tube. Minimal spectral distortion due to pile-up events is obtained up to an Incoming Count Rate of 2.5 Mcps/channel, while the maximum counting capability of energy-resolved events is 2.2 Mcps/channel.

Readout chip with RISC-V microprocessor for hybrid pixel detectors

Hybrid single-photon counting pixel detectors have recently been widely used for X-ray and ionizing particle detection in medicine, high-energy physics, and material science. Many different chips have been developed for the readout of the semiconductor pixel sensor. Typically, developed ASICs have very limited digital logic and do not provide substantial data processing. In this paper, we present the readout chip that integrates the readout channels matrix with a RISC-V-based microprocessor SoC. The designed device has been prototyped in an FPGA and sent to production in a CMOS 40 nm process. Integration of a pixel matrix with the RISC-V-based central processing unit significantly improved the detector functionality. It enabled the device to work independently without external assistive device usage and execute many algorithms, e.g., calibration, threshold scanning, and data filtering, on-chip. Communication between the CPU and the pixel matrix was carried out through the dedicated Pixel Matrix Controller with the CPU standard I/O operations usage. This specialized peripheral consists of a coprocessor responsible for precise matrix control, a data converter for data conversion acceleration, and control and status registers connected to the core data bus. Many algorithms have been developed and tested, one of which is the intelligent real-time filtering of regions of interest.

Combining and analyzing novel multi-parametric magnetic resonance imaging metrics for predicting Gleason score.

Radiologists currently subjectively examine multi-parametric magnetic resonance imaging (MP-MRI) to determine prostate tumor aggressiveness using the Prostate Imaging Reporting and Data System scoring system (PI-RADS). Recent studies showed that modified signal to clutter ratio (SCR), tumor volume, and eccentricity (elongation or roundness) of prostate tumors correlated with Gleason score (GS). No previous studies have combined the prostate tumor's shape, SCR, tumor volume, in order to predict potential tumor aggressiveness and GS. MP-MRI (T1, T2, diffusion, dynamic contrast-enhanced images) were obtained, resized, translated, and stitched to form spatially registered multi-parametric cubes. Multi-parametric signatures that characterize prostate tumors were inserted into a target detection algorithm [adaptive cosine estimator (ACE)]. Pixel-based blobbing, and labeling were applied to the threshold ACE images. Eccentricity calculation used moments of inertia from the blobs. Tumor volume was computed by counting pixels within multi parametric MRI blobs and tumor outlines based on pathologist assessment of whole mount histology. Pathology assessment of GS was performed on whole mount prostatectomy. The covariance matrix and mean of normal tissue background was computed from normal prostate. Using signatures and normal tissue statistics, the z-score, noise corrected SCR [principal component (PC), modified regularization] from each patient was computed. Eccentricity, tumor volume, and SCR were fitted to GS. Analysis of variance assesses the relationship among the variables. A multivariate analysis generated correlation coefficient (0.60 to 0.784) and P value (0.00741 to <0.0001) from fitting two sets of independent variates, namely, tumor eccentricity (the eccentricity for the largest blob, weighted average for the eccentricity) and SCR (removing 3 PCs, removing 4 PCs, modified regularization, and z-score) to GS. The eccentricity t-statistic exceeded the SCR t-statistic. The three-variable fit to GS using tumor volume (histology, MRI) yielded correlation coefficients ranging from 0.724 to 0.819 (P value <<0.05). Tumor volumes generated from histology yielded higher correlation coefficients than MRI volumes. Adding volume to eccentricity and SCR adds little improvement for fitting GS due to higher correlation coefficients among independent variables and little additional, independent information. Combining prostate tumors eccentricity with SCR relatively highly correlates with GS.

A prototype pixel readout chip working in single photon counting mode with a novel charge sharing suppression scheme

Spectral distortion due to the charge sharing effect becomes a severe issue in single-photon counting pixel detectors. The HEPS-BPIX4 prototype chip, dedicated for the HEPS in China, implements a novel architecture to mitigate charge sharing and permit spectroscopic imaging with high efficiency. In the architecture, a central pixel communicates with others in a cluster of 3 × 3 pixels. The algorithm simulation showed a charge sharing elimination accuracy better than 90%. The prototype chip has been designed in a 130 nm CMOS technology. The preliminary measurements show a charge gain of 48 mV/ke− and an equivalent noise charge of 150 e− rms. Detailed tests in a 4 × 4 pixel array for the charge sharing are performed using electrical test pulses. The hit allocation in the core four adjacent pixels of the array indicates that effective suppression of charge sharing has been realized.

Bootstrap Assessment of Crop Area Estimates Using Satellite Pixels Counting

Crop area estimates based on counting pixels over classified satellite images are a promising application of remote sensing to agriculture. However, such area estimates are biased, and their variance is a function of the error rates of the classification rule. To redress the bias, estimators (direct and inverse) relying on the so-called confusion matrix have been proposed, but analytic estimators for variances can be tricky to derive. This article proposes a bootstrap method for assessing statistical properties of such estimators based on information from a sample confusion matrix. The proposed method can be applied to any other type of estimator that is built upon confusion matrix information. The resampling procedure is illustrated in a small study to assess the biases and variances of estimates using purely pixel counting and estimates provided by both direct and inverse estimators. The method has the advantage of being simple to implement even when the sample confusion matrix is generated under unequal probability sample design. The results show the limitations of estimates based solely on pixel counting as well as respective advantages and drawbacks of the direct and inverse estimators with respect to their feasibility, unbiasedness, and variance.

Re-evaluation of the CNN-based state-of-the-art crowd-counting methods with enhancements

Crowd counting has a range of applications and it is an important task that can help with the accident prevention such as crowd crushes and stampedes in political protests, concerts, sports, and other social events. Many crown counting approaches have been proposed in the recent years. In this paper we compare five deep-learning-based approaches to crowd counting, reevaluate them and present a novel CSRNet-based approach. We base our implementation on five convolutional neural network (CNN) architectures: CSRNet, Bayesian Crowd Counting, DMCount, SFA-Net, and SGA-Net and present a novel approach by upgrading CSRNet with application of a Bayesian crowd counting loss function and pixel modeling. The models are trained and evaluated on three widely used crowd image datasets, ShanghaiTech part A, part B, and UCF-QNRF. The results show that models based on SFA-Net and DM-Count outperform state-of-the-art when trained and evaluated on the similar data, and the proposed extended model outperforms the base model with the same backbone when trained and evaluated on the significantly different data, suggesting improved robustness levels.

Medipix3 proton and carbon ion measurements across full energy ranges and at clinical flux rates in MedAustron IR1

The Medipix3, a hybrid pixel detector with a silicon sensor, has been evaluated as a beam instrumentation device with proton and carbon ion measurements in the non-clinical research room (IR1) of MedAustron Ion Therapy Center. Protons energies are varied from 62.4 to 800 MeV with 104 to 108 protons per second impinging on the detector surface. For carbon ions, energies are varied from 120 to 400 MeV/amu with 107 to 108 carbon ions per second. Measurements include simultaneous high resolution, beam profile and beam intensity with various beam parameters at up to 1000 FPS (frames per second), count rate linearity and an assessment of radiation damage after the measurement day using an x-ray tube to provide a homogeneous radiation measurement. The count rate linearity is found to be linear within the uncertainties (dominated by accelerator related sources due to special setup) for the measurements without degraders. Various frequency components are identified within the beam intensity over time firstly including 49.98 Hz with standard deviation, σ = 0.29, secondly 30.55 Hz σ = 0.55 and thirdly 252.51 Hz σ = 0.83. A direct correlation between the number of zero counting and noisy pixels is observed in the measurements with the highest flux. No conclusive evidence of long term radiation damage was found as a result of these measurements over one day.

Два способи фрактального аналізу як морфометричного методу в анатомії: спосіб підрахунку квадратів vs спосіб дилатації пікселів

Проведено порівняльний аналіз двох способів фрактального аналізу як методу морфометрії – підрахунку квадратів і дилатації пікселів. Для розробки методик фрактального аналізу використано білу речовину мозочка людини. Порівняно дві авторські модифікації методів фрактального аналізу. За результатами підрахунку фрактального індексу двома різними методами на одному зображенні встановлено, що значення фрактального індексу, обчислені методами підрахунку квадратів і дилатації пікселів, майже не розрізняються. Обидва методи дають порівнянні результати і можуть бути використані для фрактального аналізу в морфометрії з однаково високою точністю. Вибір методу залежить від особливостей зображення й досліджуваної структури. У випадках, якщо зображення легко автоматично розділити на фон і основну структуру, методом вибору є метод дилатації пікселів. Для більш складних структур і зображень може бути застосований рутинний метод підрахунку квадратів.

An Efficient Skewed Line Segmentation Technique for Cursive Script OCR

Segmentation of cursive text remains the challenging phase in the recognition of text. In OCR systems, the recognition accuracy of text is directly dependent on the quality of segmentation. In cursive text OCR systems, the segmentation of handwritten Urdu language text is a complex task because of the context sensitivity and diagonality of the text. This paper presents a line segmentation algorithm for Urdu handwritten and printed text and subsequently to ligatures. In the proposed technique, the counting pixel approach is employed for modified header and baseline detection, in which the system first removes the skewness of the text page, and then the page is converted into lines and ligatures. The algorithm is evaluated on manually generated Urdu printed and handwritten dataset. The proposed algorithm is tested separately on handwritten and printed text, showing 96.7% and 98.3% line accuracy, respectively. Furthermore, the proposed line segmentation algorithm correctly extracts the lines when tested on Arabic text.

The development and application of the test system for the silicon pixel modules in HEPS-BPIX

HEPS-BPIX is a prototype of photon counting pixel detector developed for the High Energy Photon Source. It consists of 16 silicon pixel modules which should be tested individually to ensure the function and performance. Due to various factors such as the non-uniformity of the processes and voltage drop, the response of each pixel in the silicon pixel module is not identical completely. The response difference of pixels can be minimized by the threshold calibration. This system is developed for the quality test and calibration of the silicon pixel modules. The system consists of a mother board, a control board and a data acquisition (DAQ) system. The mother board provides necessary resources including power supplies and the fanout of calibration signals. Besides, it can be used to test the connectivity by monitoring the power states. The control board reads data out and provides the clock, trigger and configuration data for the silicon pixel module. The DAQ system sends the control commands and receives the readout data through an Ethernet link. Compared with the previous readout system, this designed system has a lower noise level and better scanning curves making the calibration more accurate. And it has been successfully applied to the comparison experiments of the through silicon via and wire-bonding silicon pixel modules. The results show that this test system can be used to the quality test and calibration of the silicon pixel modules. In addition, the system can be adapted to the measurement of different pixel array detector modules.

First Principle Simulator of a Stochastically Varying Image Plane for Photon-counting High Contrast Applications

Optical and near-infrared Microwave Kinetic Inductance Detectors, or MKIDs are low-temperature detectors with inherent spectral resolution that are able to instantly register individual photons with potentially no false counts or readout noise. These properties make MKIDs transformative for exoplanet direct imaging by enabling photon-statistics-based planet-discrimination techniques as well as performing conventional noise-subtraction techniques on shorter timescales. These detectors are in the process of rapid development, and as such, the full extent of their performance enhancing potential has not yet be quantified. MKID Exoplanet Direct Imaging Simulator, or MEDIS, is a general-purpose end-to-end numerical simulator for high-contrast observations with MKIDs. The simulator exploits current optical propagation libraries and augments them with a new MKIDs simulation module to provide a pragmatic model of many of the degradation effects present during the detection process. We use MEDIS to demonstrate how changes in various MKID properties affect the contrast-separation performance when conventional differential imaging techniques are applied to low-flux, short duration observations. We show that to improve performance at close separations will require increasing the maximum count rate or pixel sampling when there is high residual flux after the coronagraph. We predict that taking pixel yield from the value achieved by current instruments of 80% and increasing it to 100% would result in an improvement in contrast of a factor of ∼4 at 3λ/D and ∼8 at 6λ/D. Achieving better contrast performance in this low flux regime would then require exploiting the information encoded in the photon arrival time statistics.

The TSV process in the hybrid pixel detector for the High Energy Photon Source

HEPS-BPIX3 is the third prototype of a single-photon counting pixel detector with 1.4 million pixels developed for applications using synchrotron light sources. It follows the previous prototypes with a pixel size of 150μm×150μm and frame rate up to 1.2 kHz at 20-bit dynamic range. We started to upgrade it with the through silicon via (TSV) process to reduce the insensitive gap between modules. The TSV process drills vias at the pads of the readout chip, and makes connections between the front and back sides. The redistribution layer (RDL) and bump bonding are performed at the bottom of readout chip to connect the control, readout signals and power supplies to the PCB. By using this so-called three-dimensional (3D) integration techniques, the insensitive area of the module is reduced from 26.3% to 11.8%. The assembled modules have been tested with X-ray and synchrotron light source, and the results show that the readout chips work well following the TSV process without any measurable performance degradation.

Count rate capabilities of polycrystalline silicon photon counting detectors for CBCT applications—a theoretical study

The signal-to-noise properties of active matrix, flat-panel imagers (AMFPIs) limit the imaging performance of this x-ray imaging technology under conditions of low dose per image frame. This limitation can affect cone-beam computed tomography (CBCT) procedures where an AMFPI is used to acquire hundreds of image frames to form a single volumetric data set. An approach for overcoming this limitation is to replace the energy-integrating pixel circuits of AMFPI arrays with photon counting pixel circuits which examine the energy of each x-ray interaction and count those events whose signals exceed user-defined energy thresholds. A promising material for fabricating the circuits of such photon-counting detectors (PCDs) is polycrystalline silicon (poly-Si)—a semiconductor that facilitates economic manufacture of large area, monolithic arrays of the size presently provided by AMFPIs as well as provides good radiation damage resistance. In this paper, results are reported from a theoretical investigation of the potential for poly-Si PCDs to satisfy the count rate needs, while maintaining good energy resolution, of two CBCT applications—CBCT used for breast imaging and kilo-voltage CBCT used for providing localization information in image guided radiotherapy (referred to as BCT and kV-CBCT, respectively). The study focused on the performance of the critical first component of a PCD pixel circuit, the amplifier, under conditions relevant to the two applications. The study determined that, compared to the average input fluxes associated with BCT and kV-CBCT, a promising amplifier design employing poly-Si thin-film transistors can provide count rates two and four times in excess of those levels, respectively, assuming a dead time loss of 10%. In addition, calculational estimates based on foreseeable poly-Si circuit densities suggest that it should be possible to include sufficient circuitry to support 2 and 3 energy thresholds per pixel, respectively. Finally, prospects for further improvements are discussed.

Single layer Compton camera based on Timepix3 technology

The Compton camera concept is based on reconstruction of recorded Compton scattering events for incoming gamma rays. The camera usually consist of two or more position (2D) and energy sensitive detectors. The Compton scattering of the incoming gamma ray recoiling an electron occurs in the first detector. The position and energy of recoiled electron is recorded. The scattered gamma ray continues to the next detector where it is absorbed and its energy and position is recorded too. Knowing both positions and energies the scattering angle can be calculated using the Compton equation. By detecting multiple events the position and image of the gamma source can be reconstructed. The Compton scattering and absorption of the scattered gamma can occur within a single detector too. Such events can be used for reconstruction only if the detector provides information on 3D positions of both events along with their energies. The Timepix3, a hybrid single photon counting pixel detector, is perfect device for such measurements. It can record time-of-arrival (ToA) and energy of incident gamma rays simultaneously in each pixel. In this article we present a concept of miniaturized single layer Compton camera consisting of a single Timepix3 detector with a thick 2 mm CdTe sensor. Thanks to Timepix3 high resolution ToA measurement (1.6 ns), it is possible to measure the drift time of charge transport within the sensor and thus determine the vertical position (depth) of both interactions. By knowing both energy and position of the events in the sensor, we can reconstruct the image of the gamma source. The angular resolution of the presented Compton camera depends on the detected energy and reaches the order of a few degrees.

HEPS-BPIX2: The hybrid pixel detector upgrade for high energy photon source in China

The High Energy Photon Source (HEPS) is a new research facility currently under construction in Beijing, China. HEPS-BPIX2 is the second prototype of photon counting pixel detector developed at Institute of High Energy Physics (IHEP) to comply with the requirements of the HEPS. It follows the first prototype, HEPS-BPIX, with a pixel size of 150μm x 150μm and frame rate up to 1.2 kHz at 20-bit dynamic range, but upgrades with transmission control protocol (TCP) hardware stack on 10 Gigabit Ethernet (10 GbE) for large-area multi-modules system. One million-pixel detector with 16 modules, covering an area of 16.32 cm x 18.3 cm, is integrated, and it has demonstrated the basic functionality with X-ray and synchrotron light. The readout system is organized in parallel with groups and in daisy-chain in each group, achieving 23 Gbps data at full 1.2 kHz frame rate.

Dynamic space utilization for lame and non-lame gestating sows estimated by the lying-standing sequence

The objective of this study was to estimate the dynamic space utilization for lame and non-lame sows using their lying-standing postural sequence profile. Eighty-five sows (parity 0.9 ± 1.14; range 0 to 4) were used. Sows were moved to a pen on 30, 60 and 90 days of gestation and a ceiling mounted camera was installed above the pen to record one lying-standing event per sow. Observations ceased when the sow lied and stood, or 2.5 h elapsed from recording commencement. Additionally, each sow was evaluated for walking lameness while moving from their gestation stall to the pen. Still frames were captured from the sows’ lying and standing sequences and were combined into a single image and measured by counting pixels from contouring the sows’ body (CONTOUR), overlaying a grid on the sow image and counting any square including any part of the sow (FULL-GRID) and only counting any square that was half full or more (HALF-GRID). The space utilized while turning around was calculated by measuring the sows’ length from snout to the base of the tail and using that length as the diameter of a circle (D-PIVOT), or as the radius of a circle (R-PIVOT). Parity was re-classified as 0, 1, and 2+. There were no observed differences in the dynamic space utilized to lie, stand or turn around between lame and non-lame sows (P > 0.05). On average, sows used 1.2 ± 0.47 m2 to lie and 1.3 ± 0.46 m2 to stand. There was no difference between the CONTOUR and HALF-GRID methods (P > 0.05); however, using the FULL-GRID sows required 0.3 m2 more floor area to lie and stand compared with the other measuring methods (P < 0.05). Space used to turn around differed between measuring method (P < 0.05). Sows required 1.9 ± 0.18 m2 for D-PIVOT and 7.3 ± 0.18 m2 for R-PIVOT to turn around. Space utilized to lie-down and stand-up increased as gestation progressed (P < 0.05). Under the conditions of this study, lameness did not influence dynamic space utilization; however, lameness recorded was relatively mild and might not have been sufficiently severe to significantly affect the results. These results could be important in decision-making process for housing specifications regarding US sow gestation housing.