Image Quality Measures Research Articles

Dynamic Differential Image Circle Diameter Measurement Precision Assessment: Application to Burning Droplets.

Dynamic measurement precision assessment has been achieved for a differential circle measurement application. Differential circle diameter measurement, in image analysis, typically requires fitting a circle model that optimizes for image distortions, defects or occlusions. The differential task occurs when precise measurements of diameter change are required given object size variation with time. An automated system was designed to provide diameter measurements and associated measurement precision of images of a fuel droplet undergoing combustion in zero gravity for the FLEX-2 dataset. An image gradient-based, least-squares boundary point fitting method to a circle or ellipse model is used for diameter measurement. The presence of soot aggregates poses significant challenges for diameter measurements when it occludes part of the droplet boundary. The precision of the diameter measurements depends upon the image quality. Using synthetic image simulations that model the soot behavior, we developed a model based on image quality measures that assesses the measurement precision for each individual diameter measurement. Thus, diameter measurements with precision assessments were made available for follow-up scientific analysis. The algorithm's success rate for measurable runs was 98%. In cases of limited occlusion, a measurement precision of ±0.2 pixels for the FLEX-2 dataset was achieved.

Compare different techniques to retrieve image from database using MATLAB

Newly World Wide Web technologies, there is need to secure data. For securing data cryptography and other relevant techniques were introduced. Multimedia data stream, traditional textual based encryption schemes are not successful so there is need to develop new encryption schemes. During transmission and storage over a network, multimedia content such as digital images and other information are vulnerable to unauthorized access. The images used may be gray or color scale images. There are many measures for testing image quality, like as the mean structural similarity, and mean absolute error, Mean Square Error (MSE), and Peak Signal-to-Noise Ratio (PSNR). These are computed by averaging the squared intensity differences of distorted and original image pixels, along with the related quantity of the PSNR. Results of experiments show that same size images are efficiently encrypted with reliable maximum PSNR as compared with different size images. MATLAB2013a is used for simulation purpose. As refereed by the simulation results, the proposed system not only shows the efficiency in hiding the attributes but also provides better cover image selection.

Smartphone imaging repository: a novel method for creating a CT image bank

BackgroundImaging repositories are commonly attached to ongoing clinical trials, but capturing, transmitting, and storing images can be complicated and labor-intensive. Typical methods include outdated technologies such as compact discs. Electronic file transfer is becoming more common, but even this requires hours of staff time on dedicated computers in the radiology department.MethodsWe describe and test an image capture method using smartphone camera video-derived images of brain computed tomography (CT) scans of traumatic intracranial hemorrhage. The deidentified videos are emailed or uploaded from the emergency department for central adjudication. We selected eight scans, mild moderate, and severe subdural and multicompartmental hematomas and mild and moderate intraparenchymal hematomas. Ten users acquired data using seven different smartphones. We measured the time in seconds it took to capture and send the files. The primary outcomes were hematoma volume measured by ABC/2, Marshall scale, midline shift measurement, image quality by a contrast-to-noise ratio (CNR), and time to capture. A radiologist and an imaging scientist applied the ABC/2 method and calculated the Marshall scale and midline shift on the data acquired on different smartphones and the PACS in a randomized order. We calculate the intraclass correlation coefficient (ICC). We measured image quality by calculating the contrast-to-noise ratio (CNR). We report summary statistics on time to capture in the smartphone group without a comparator.ResultsICC for lesion volume, midline shift, and Marshall score were 0.973 (95% CI 0.931, 0.994), 0.998 (95% CI: 0.996, 0.999), and 0.973 (0.931, 0.994), respectively. Lesion conspicuity was not different among the image types via assessment of CNR using the Friedman test, {lambda }^{2} of 24.8, P = < .001, with a small Kendall’s W effect size (0.591). Mean (standard deviation) time to capture and email the video was 60.1 (24.3) s.ConclusionsTypical smartphones may produce video image quality high enough for use in a clinical trial imaging repository. Video capture and transfer takes only seconds, and hematoma volumes, Marshall scales, and image quality measured on the videos did not differ significantly from those calculated on the PACS.

Abdominopelvic CT Image Quality: Evaluation of Thin (0.5-mm) Slices Using Deep Learning Reconstruction.

BACKGROUND. Because thick-section images (typically 3-5 mm) have low image noise, radiologists typically use them to perform clinical interpretation, although they may additionally refer to thin-section images (typically 0.5-0.625 mm) for problem solving. Deep learning reconstruction (DLR) can yield thin-section images with low noise. OBJECTIVE. The purpose of this study is to compare abdominopelvic CT image quality between thin-section DLR images and thin- and thick-section hybrid iterative reconstruction (HIR) images. METHODS. This retrospective study included 50 patients (31 men and 19 women; median age, 64 years) who underwent abdominopelvic CT between June 15, 2020, and July 29, 2020. Images were reconstructed at 0.5-mm section using DLR and at 0.5-mm and 3.0-mm sections using HIR. Five radiologists independently performed pairwise comparisons (0.5-mm DLR and either 0.5-mm or 3.0-mm HIR) and recorded the preferred image for subjective image quality measures (scale, -2 to 2). The pooled scores of readers were compared with a score of 0 (denoting no preference). Image noise was quantified using the SD of ROIs on regions of homogeneous liver. RESULTS. For comparison of 0.5-mm DLR images and 0.5-mm HIR images, the median pooled score was 2 (indicating a definite preference for DLR) for noise and overall image quality and 1 (denoting a slight preference for DLR) for sharpness and natural appearance. For comparison of 0.5-mm DLR and 3.0-mm HIR, the median pooled score was 1 for the four previously mentioned measures. These assessments were all significantly different (p < .001) from 0. For artifacts, the median pooled score for both comparisons was 0, which was not significant for comparison with 3.0-mm HIR (p = .03) but was significant for comparison with 0.5-mm HIR (p < .001) due to imbalance in scores of 1 (n = 28) and -1 (slight preference for HIR, n = 1). Noise for 0.5-mm DLR was lower by mean differences of 12.8 HU compared with 0.5-mm HIR and 4.4 HU compared with 3.0-mm HIR (both p < .001). CONCLUSION. Thin-section DLR improves subjective image quality and reduces image noise compared with currently used thin- and thick-section HIR, without causing additional artifacts. CLINICAL IMPACT. Although further diagnostic performance studies are warranted, the findings suggest the possibility of replacing current use of both thin- and thick-section HIR with the use of thin-section DLR only during clinical interpretations.

MtFRC: depth-dependent resolution quantification of image features in 3D fluorescence microscopy.

Quantifying lateral resolution as a function of depth is important in the design of 3D microscopy experiments. However, for many specimens, resolution is non-uniform within the same optical plane because of factors such as tissue variability and differential light scattering. This precludes application of a simple resolution metric to the image as a whole. In such cases, it can be desirable to analyse resolution only within specific, well-defined features. An algorithm and software are presented to characterize resolution as a function of depth in features of arbitrary shape in 3D samples. The tool can be used to achieve an objective comparison between different preparation methods, imaging parameters, and optical systems. It can also inform the design of experiments requiring resolution of structures at a specific scale. The method is demonstrated by quantifying the improvement in resolution of two-photon microscopy over confocal in the central brain of Drosophila melanogaster. Measurement of image quality increases by tuning a single parameter, laser power, is also shown. An ImageJ plugin implementation is provided for ease of use via a simple Graphical User Interface, with outputs in table, graph, and colourmap formats. Software and source code are available at https://www.imperial.ac.uk/rowlands-lab/resources/.

Wavefront measurement of a large aperture high image quality off-axis Fresnel lens.

Large aperture off-axis Fresnel lens will play an important role in the future 10 m scale aperture transmission space telescope system. Improving diffraction efficiency and wavefront image quality is always the goal of engineering applications. A 4-level off-axis fresnel lens with Ф350 mm effective aperture was fabricated through overlay etching technique by laser direct writing system. The wavefront aberration characteristics of the off-axis Fresnel lens at 632.8 nm wavelength are analyzed and discussed in detail, and the large aperture off-axis Fresnel lenses wavefront aberration measurement scheme, including a high-precision plane reflector, measured LAOFL, CGH, interferometer and laser tracker to compensate for certain low-order aberrations caused by LAOFL imperfect imaging, is proposed. Wavefront aberration of 0.020 λ(1/50 λ) RMS was achieved. This work presented the best results to our knowledge among the same field with similar aperture in open publications and provided a strong foundation for the future 10 m scale aperture transmission space telescope system.

Full-Reference Image Quality Expression via Genetic Programming.

Full-reference image quality measures are a fundamental tool to approximate the human visual system in various applications for digital data management: from retrieval to compression to detection of unauthorized uses. Inspired by both the effectiveness and the simplicity of hand-crafted Structural Similarity Index Measure (SSIM), in this work, we present a framework for the formulation of SSIM-like image quality measures through genetic programming. We explore different terminal sets, defined from the building blocks of structural similarity at different levels of abstraction, and we propose a two-stage genetic optimization that exploits hoist mutation to constrain the complexity of the solutions. Our optimized measures are selected through a cross-dataset validation procedure, which results in superior performance against different versions of structural similarity, measured as correlation with human mean opinion scores. We also demonstrate how, by tuning on specific datasets, it is possible to obtain solutions that are competitive with (or even outperform) more complex image quality measures.

Increasing Source-Object Distance: A Computed Radiography-based Strategy to Reducing Radiation Dose in Occipital-Frontal Skull X-Ray

Introduction: Exploring potential optimization strategies and developing evident practices is critical. Previous studies show that radiation dose can be reduced by increasing the source-image distance (SID). Although most studies use digital radiography, many hospitals in underdeveloped countries still use computed radiography (CR). Therefore, research will investigate the relationship between SID and Entrance surface dose (ESD) using the CR. Methods: This study involved the measurement of radiation dose and image quality of a radiological procedure performed at a reference SID; 100cm and the tested SIDs; 110cm, 120cm, and 130cm, using constant technical factors (70kVp, 25mAs, grid). A LiF; Mg Ti thermoluminescence dosimeter (TLD-100) chip was placed in the center of the radiation field of the OF10° skull radiography examination to measure ESD. Image quality was assessed using the European Commission guidelines and graded using relative visual assessment analysis (VGA). Results: Significant ESD reduction from 21% and 45% when SID was increased from 100cm to 130cm (p &lt;0.001), where SID was negatively correlated with ESD (r= - 0.98). The VGA scores showed no statistical difference in the image quality of the OF10° skull radiography examination for the tested and reference images (p=0.21). VGA scores for 120cm images showed the highest image quality among the SIDs tested with a dose reduction of 37%. Conclusion: ESD was statically reduced when SID was increased from 100cm to 130cm, while image quality was diagnostically acceptable. The study suggests that 120cm is the optimal SID when both dose and image quality are considered.

Application of three-dimensional (3D) magnetic resonance (MR) Multi-Echo iN Steady-state Acquisition sequences in preoperative evaluation of lumbar disc herniation: a prospective study.

Conventional spinal magnetic resonance imaging (MRI) cannot provide accurate diagnosis and surgical planning; thin-layer scanning can enhance the diagnostic efficacy. This study aimed to investigate the value of 3-dimensional (3D) magnetic resonance (MR) in preoperative evaluation of lumbar disc herniation, with a focus on the application of Multi-Echo iN Steady-state Acquisition (MENSA) sequence. A total of 51 patients who underwent lumbar disc herniation surgery in West China Hospital of Sichuan University from June 2021 to December 2021 were prospectively enrolled. A cross-sectional study was conducted on those patients. The Cube group was scanned using 3D-FSE-Cube sequence, the Cube stir group was scanned using 3D-FSE-Cube Short Tau Inversion Recovery (STIR) sequence, and the MENSA group was scanned using MENSA sequence. Signal and noise values of nerve, herniated disc, ligamentum flavum (LF), and soft tissue were measured on the 3 groups. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Objective scores were calculated by analysis of variance (ANOVA). Image quality was scored by a 5-point method. Friedman test was used to compare subjective scores, and Kappa test was used to evaluate the consistency of 2 readers' scores. The nerve root SNRs in the MENSA and Cube stir groups were higher than that in the Cube group (P<0.01), but there was no substantial statistical difference between the 2 groups. The herniated disc and LF SNRs of the MENSA group were greater than those of the Cube stir and Cube groups (P<0.01). Soft tissue SNR was greater in the MENSA group compared with the Cube stir group (P<0.01), which was greater than the SNR in the Cube group (P<0.01). The nerve root CNR of the Cube group (102.88±73.19) was greater than that of the MENSA group (55.98±25.26, P<0.01), which was higher than the CNR in the Cube Stir group (29.42±16.22, P<0.01). The herniated disc CNR was higher in the MENSA and Cube groups than that in the Cube Stir group. The CNR of LF was greater in the MENSA group (37.71±16.87) compared to the Cube group (29.76±25.73, P=0.03), which was greater than that in the Cube stir group (10.50±7.75, P<0.01). Among the subjective ratings of 2 reviewers, MENSA sequence scored highest in the qualitative measures of image quality. In the consistency test, the Kappa values of 2 readers for 3 groups of images were all greater than 0.73, indicating good consistency. The differences of subjective scores among all groups were statistically significant (P<0.05). Overall, it was indicated that the consistency test results of the 2 readers were statistically significant and consistent. The MENSA group had the highest accuracy in diagnosing nerve compression. In addition, MENSA sequence ranked highest among the 3 sequences with 94.1% diagnostic accuracy. The preoperative 3D MRI MENSA sequence can clearly depict the nerve roots and offer desirable contrast between the nerve roots, LF, bone, and intervertebral discs (IVDs). Patients with lumbar degeneration can effectively benefit from MENSA sequence since it provides useful imaging information to help understand disc herniation and compression of adjacent tissues when developing preoperative surgical strategies.

Anatomical evaluation of deep-learning synthetic computed tomography images generated from male pelvis cone-beam computed tomography.

To improve cone-beam computed tomography (CBCT), deep-learning (DL)-models are being explored to generate synthetic CTs (sCT). The sCT evaluation is mainly focused on image quality and CT number accuracy. However, correct representation of daily anatomy of the CBCT is also important for sCTs in adaptive radiotherapy. The aim of this study was to emphasize the importance of anatomical correctness by quantitatively assessing sCT scans generated from CBCT scans using different paired and unpaired dl-models. Planning CTs (pCT) and CBCTs of 56 prostate cancer patients were included to generate sCTs. Three different dl-models, Dual-UNet, Single-UNet and Cycle-consistent Generative Adversarial Network (CycleGAN), were evaluated on image quality and anatomical correctness. The image quality was assessed using image metrics, such as Mean Absolute Error (MAE). The anatomical correctness between sCT and CBCT was quantified using organs-at-risk volumes and average surface distances (ASD). MAE was 24 Hounsfield Unit (HU) [range:19-30 HU] for Dual-UNet, 40 HU [range:34-56 HU] for Single-UNet and 41HU [range:37-46 HU] for CycleGAN. Bladder ASD was 4.5mm [range:1.6-12.3mm] for Dual-UNet, 0.7mm [range:0.4-1.2mm] for Single-UNet and 0.9mm [range:0.4-1.1mm] CycleGAN. Although Dual-UNet performed best in standard image quality measures, such as MAE, the contour based anatomical feature comparison with the CBCT showed that Dual-UNet performed worst on anatomical comparison. This emphasizes the importance of adding anatomy based evaluation of sCTs generated by dl-models. For applications in the pelvic area, direct anatomical comparison with the CBCT may provide a useful method to assess the clinical applicability of dl-based sCT generation methods.

Blind 3D-Synthesized Image Quality Measurement by Analysis of Local and Global Statistical Properties

Blind 3D-Synthesized Image Quality Measurement by Analysis of Local and Global Statistical Properties

Visual Enhancement of Underwater Images Using Transmission Estimation and Multi-Scale Fusion

The demand for the exploration of ocean resources is increasing exponentially. Underwater image data plays a significant role in many research areas. Despite this, the visual quality of underwater images is degraded because of two main factors namely, backscattering and attenuation. Therefore, visual enhancement has become an essential process to recover the required data from the images. Many algorithms had been proposed in a decade for improving the quality of images. This paper aims to propose a single image enhancement technique without the use of any external datasets. For that, the degraded images are subjected to two main processes namely, color correction and image fusion. Initially, veiling light and transmission light is estimated to find the color required for correction. Veiling light refers to unwanted light, whereas transmission light refers to the required light for color correction. These estimated outputs are applied in the scene recovery equation. The image obtained from color correction is subjected to a fusion process where the image is categorized into two versions and applied to white balance and contrast enhancement techniques. The resultants are divided into three weight maps namely, luminance, saliency, chromaticity and fused using the Laplacian pyramid. The results obtained are graphically compared with their input data using RGB Histogram plot. Finally, image quality is measured and tabulated using underwater image quality measures.

Optimizing effective dose and image quality in cone beam CT sialography

The purpose of this study was to develop protocols that optimize patient radiation dose and image quality for cone beam computed tomographic (CBCT) sialography for the major salivary glands. Radiation absorbed dose measurements were repeated in triplicate using 25 sites in the head and neck of a Radiation ANalog DOsimetry system (RANDO) phantom, and effective doses were calculated across a range of peak kilovoltage (kVp) and milliamperage (mA) settings using an 8 cm (diameter) by 5 cm (height) field of view (FOV) for submandibular imaging and an 8 cm (diameter) by 8 cm (height) FOV for parotid imaging. Image signal difference-to-noise ratio (SDNR) was determined, and the figure-of-merit (FOM), a measure of image quality, was calculated. For submandibular sialography, 85 kVp and 6 mA were chosen as the optimal exposure parameters, resulting in a mean effective dose of 82.47 µSv and a mean SDNR of 13.86, with a mean FOM of 2.33 µSv-1. For parotid sialography, 70 kVp and 6 mA were chosen, and these settings resulted in a mean effective dose of 39.99 µSv, a mean SDNR of 17.43, and a mean FOM of 7.60 µSv-1. Low-dose 3-dimensional sialography with high image quality and minimal effective dose can be delivered using CBCT with localized, small FOVs.

Dose optimization and image quality measurement in digital abdominal radiography

Digital radiographic (DR) imaging systems, which have an important place in the diagnosis and monitoring of diseases, are frequently used in various clinical applications today and can produce adequate image quality using a wide range of exposure levels. Overexposure without effective improvement in image quality can produce high dose levels that adversely affect both diagnostic radiology efficiency and health; therefore, experimental data analysis is a useful, ongoing process for providing information about the adequacy of radiation exposure. The aim of this study is to evaluate the quality performance of digital radiographic systems using an objective image quality test device. For this purpose, the effect of each radiographic factor on reducing the radiation dose is investigated to provide diagnostically acceptable quality images.

Evaluation of image quality, organ doses, effective dose, and cancer risk from pediatric brain CT scans

purposeThe present study was conducted to assess organ doses, effective dose, and image quality, and to estimate the risk of exposure-induced cancer death (REID) in pediatric brain computed tomography examinations. MethodsThis investigation was performed on 179 pediatric patients (99 men and 80 women) under 12 years old who underwent non-contrast brain CT scans. Patients were classified into four age groups of ≤ 1, 2–5, 6–9, and 10–12 years old. Organ doses and effective doses were calculated using the ImpactDose program. Cancer risk models presented in the BEIR VII report were used to estimate REID values. Image quality assessment in this study was performed by measuring image quality parameters such as noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). ResultsThe highest organ dose in all age groups belonged to the brain. The mean REID values were 12.34 per 100,000 males and 16.77 per 100,000 females. REID values decreased with the increasing age of patients in both genders and were higher for female children than male children. The mean SNR of gray matter, SNR of white matter, and CNR were 11.04, 10.5, and 2.31, respectively. ConclusionsAccording to the results of this study, brain CT scans in children are associated with an increased potential risk of cancer. Therefore, minimizing unnecessary radiation exposure in pediatric patients and using alternative imaging modalities are of particular importance. Moreover, optimizing the radiation parameters while maintaining the diagnostic image quality in children should be considered.

Modified three-term conjugate gradient algorithm and its applications in image restoration

In image restoration, the goal is often to bring back a high-quality version of an image from a lower-quality copy of it. In this article, we will investigate one kind of recovery issue, namely recovering photos that have been blurred by noise in digital photographs (sometimes known as "salt and pepper" noise). When subjected to noise at varying frequencies and intensities (30,50,70,90). In this paper, we used the conjugate gradient algorithm to Restorative images and remove noise from them, we developed the conjugate gradient algorithm with three limits using the conjugate condition of Dai and Liao, where the new algorithm achieved the conditions for descent and global convergence under some assumptions. According to the results of the numerical analysis, the recently created approach is unequivocally superior to both the fletcher and reeves (FR) method and the fletcher and reeves three-term (TTFR) metod. Use the structural similarity index measure (SSIM), which is used to measure image quality and the higher its value, the better the result. The original image was compared with all the noisy images and each according to the percentage of noise as well as the images processed with the four methods.

Comparing image quality of five breast tomosynthesis systems based on radiologists' reviews of phantom data.

Previous studies have shown differences in technical image quality between digital breast tomosynthesis (DBT) systems. However, quantitative image quality measurements may not necessarily fully reflect the clinical performance of DBT. To study the subjective image quality of five DBT systems manufactured by Fujifilm, GE, Hologic, Planmed, and Siemens using phantom images. A TOR MAM test object with polymethyl methacrylate plates was imaged on five DBT systems from different vendors. Three DBT acquisitions were performed at mean glandular doses of 1.0 mGy, 2.0 mGy, and 3.5 mGy while maintaining a constant phantom set-up. Eight DBT acquisitions with different test plate positions and phantom set-up thicknesses were performed at clinically applied dose levels. Additionally, three conventional two-dimensional mammogram images were acquired with different phantom thicknesses. Six radiologists ranked the systems based on the visibilities of the targets seen in the phantom images. In the DBT acquisitions performed at comparable dose levels, one system differed significantly from all other systems in microcalcification scores. When using site-specific DBT protocols, significant differences were found between the devices for microcalcification, filament, and low-contrast targets. A strong correlation was observed between the reviewer scores and radiation doses in DBT acquisitions, whereas no such correlation was observed in the 2D acquisitions. In DBT acquisitions, dose level was found to be a major factor explaining image quality differences between the systems, regardless of other acquisition parameters. Most DBT systems performed equally well at similar dose levels.

Visibility enhancement of underwater images based on polarization common-mode rejection of a highly polarized target signal.

Underwater active polarization imaging is promising due to its effect of significantly descattering. Polarization-difference is commonly used to filter out backscattered noise. However, the polarization common-mode rejection of target signal has rarely been utilized. In this paper, via taking full advantage of this feature of Stokes vectors S2 which ably avoids interference from target light, the spatial variation of the degree of polarization of backscattered light is accurately estimated, and the whole scene intensity distribution of background is reconstructed by Gaussian surface fitting based on least square. Meanwhile, the underwater image quality measure is applied as optimization feedback, through iterative computations, not only sufficiently suppresses backscattered noise but also better highlights the details of the target. Experimental results demonstrate the effectiveness of the proposed method for highly polarized target in strongly scattering water.

Underwater Optical-Sonar Image Fusion Systems.

Unmanned underwater operations using remotely operated vehicles or unmanned surface vehicles are increasing in recent times, and this guarantees human safety and work efficiency. Optical cameras and multi-beam sonars are generally used as imaging sensors in underwater environments. However, the obtained underwater images are difficult to understand intuitively, owing to noise and distortion. In this study, we developed an optical and sonar image fusion system that integrates the color and distance information from two different images. The enhanced optical and sonar images were fused using calibrated transformation matrices, and the underwater image quality measure (UIQM) and underwater color image quality evaluation (UCIQE) were used as metrics to evaluate the performance of the proposed system. Compared with the original underwater image, image fusion increased the mean UIQM and UCIQE by 94% and 27%, respectively. The contrast-to-noise ratio was increased six times after applying the median filter and gamma correction. The fused image in sonar image coordinates showed qualitatively good spatial agreement and the average IoU was 75% between the optical and sonar pixels in the fused images. The optical-sonar fusion system will help to visualize and understand well underwater situations with color and distance information for unmanned works.

The development of ultra-high field MRI guidance technology for neuronavigation.

Magnetic resonance imaging at 7T offers improved image spatial and contrast resolution for visualization of small brain nuclei targeted in neuromodulation. However, greater image geometric distortion and a lack of compatible instrumentation preclude implementation. In this report, the authors detail the development of a stereotactic image localizer and accompanying imaging sequences designed to mitigate geometric distortion, enabling accurate image registration and surgical planning of basal ganglia nuclei. Magnetization-prepared rapid acquisition with gradient echo (MPRAGE), fast gray matter acquisition T1 inversion recovery (FGATIR), T2-weighted, and T2*-weighted sequences were optimized for 7T in 9 human subjects to visualize basal ganglia nuclei, minimize image distortion, and maximize target contrast-to-noise and signal-to-noise ratios. Extracranial spatial distortions were mapped to develop a skull-contoured image localizer embedded with spherical silicone fiducials for improved MR image registration and target guidance. Surgical plan accuracy testing was initially performed in a custom-developed MRI phantom (n = 5 phantom studies) and finally in a human trial. MPRAGE and T2*-weighted sequences had the best measures among global measures of image quality (3.8/4, p < 0.0001; and 3.7/4, p = 0.0002, respectively). Among basal ganglia nuclei, FGATIR outperformed MPRAGE for globus pallidus externus (GPe) visualization (2.67/4 vs 1.78/4, p = 0.008), and FGATIR, T2-weighted imaging, and T2*-weighted imaging outperformed MPRAGE for substantia nigra visualization (1.44/4 vs 2.56/4, p = 0.04; vs 2.56/4, p = 0.04; vs 2.67/4, p = 0.003). Extracranial distortion was lower in the head's midregion compared with the base and apex ( 1.17-1.33 mm; MPRAGE and FGATIR, p < 0.0001; T2-weighted imaging, p > 0.05; and T2*-weighted imaging, p = 0.013). Fiducial placement on the localizer in low distortion areas improved image registration (fiducial registration error, 0.79-1.19 mm; p < 0.0001) and targeting accuracy (target registration error, 0.60-1.09 mm; p = 0.04). Custom surgical software and the refined image localizer enabled successful surgical planning in a human trial (fiducial registration error = 1.0 mm). A skull-contoured image localizer that accounts for image distortion is necessary to enable high-accuracy 7T imaging-guided targeting for surgical neuromodulation. These results may enable improved clinical efficacy for the treatment of neurological disease.