Static Images Research Articles

Adaptive frequency driving scan driver based on a‐InGaZnO TFTs for extremely low‐power displays

AbstractIn this paper, we propose a novel scan driver combined with a logic circuit using amorphous indium‐gallium‐zinc‐oxide (a‐InGaZnO) thin‐film transistors (TFTs) in order to enhance the electrical stability and reduce power consumption in display panels. The latest mobile displays with high resolution and refresh rates consume more battery power, which inevitably limits portability and usability. The proposed scan driver can mask the signal by combining the output stage with a logic circuit, thereby blocking the output pulse for static images. This allows the display panel to operate in a partial driving mode depending on the display content. Due to the masking of the scan driver's output pulses, the connected pixel circuits are consistently maintained in the same state as the previous frame, leading to a lower refresh rate and reduced power consumption. Furthermore, by constructing additional control signals, the proposed scan driver can operate stably in depletion mode under a ∆VTH = −3 V.

Color image watermarking using vector SNCM-HMT

An image watermarking scheme is typically evaluated using three main conflicting characteristics: imperceptibility, robustness, and capacity. Developing a good image watermarking method is challenging because it requires a trade-off between these three basic characteristics. In this paper, we proposed a statistical color image watermarking based on robust discrete nonseparable Shearlet transform (DNST)-fast quaternion generic polar complex exponential transform (FQGPCET) magnitude and vector skew-normal-Cauchy mixtures (SNCM)-hidden Markov tree (HMT). The proposed watermarking system consists of two main parts: watermark inserting and watermark extraction. In watermark inserting, we first perform DNST on R, G, and B components of color host image, respectively. We then compute block FQGPCET of DNST domain color components, and embed watermark signal in DNST-FQGPCET magnitudes using multiplicative approach. In watermark extraction, we first analyze the robustness and statistical characteristics of local DNST-FQGPCET magnitudes of color image. We then observe that, vector SNCM-HMT model can capture accurately the marginal distribution and multiple strong dependencies of local DNST-FQGPCET magnitudes. Meanwhile, vector SNCM-HMT parameters can be computed effectively using variational expectation–maximization (VEM) parameter estimation. Motivated by our modeling results, we finally develop a new statistical color image watermark decoder based on vector SNCM-HMT and maximum likelihood (ML) decision rule. Experimental results on extensive test images demonstrate that the proposed statistical color image watermarking provides a performance better than that of most of the state-of-the-art statistical methods and some deep learning approaches recently proposed in the literature.

DFCNet +: Cross-modal dynamic feature contrast net for continuous sign language recognition

In sign language communication, the combination of hand signs and facial expressions is used to convey messages in a fluid manner. Accurate interpretation relies heavily on understanding the context of these signs. Current methods, however, often focus on static images, missing the continuous flow and the story that unfolds through successive movements in sign language. To address this constraint, our research introduces the Dynamic Feature Contrast Net Plus (DFCNet+), a novel model that incorporates both dynamic feature extraction and cross-modal learning. The dynamic feature extraction module of DFCNet+ uses dynamic trajectory capture to monitor and record motion across frames and apply key features as an enhancement tool that highlights pixels that are critical for recognizing important sign language movements, allowing the model to follow the temporal variation of the signs. In the cross-modal learning module, we depart from the conventional approach of aligning video frames with textual descriptions. Instead, we adopt a gloss-level alignment, which provides a more detailed match between the visual signals and their corresponding text glosses, capturing the intricate relationship between what is seen and the associated text. The enhanced proficiency of DFCNet+ in discerning inter-frame details translates to heightened precision on benchmarks such as PHOENIX14, PHOENIX14-T and CSL-Daily. Such performance underscores its advantage in dynamic feature capture and inter-modal learning compared to conventional approaches to sign language interpretation. Our code is available at https://github.com/fyzjut/DFCNet_Plus.

Artificial intelligence applications in ophthalmic surgery.

Technologies in healthcare incorporating artificial intelligence tools are experiencing rapid growth in static-image-based applications such as diagnostic imaging. Given the proliferation of artificial intelligence (AI)-technologies created for video-based imaging, ophthalmic microsurgery is likely to experience significant benefits from the application of emerging technologies to multiple facets of the care of the surgical patient. Proof-of-concept research and early phase clinical trials are in progress for AI-based surgical technologies that aim to provide preoperative planning and decision support, intraoperative image enhancement, surgical guidance, surgical decision-making support, tactical assistive technologies, enhanced surgical training and assessment of trainee progress, and semi-autonomous tool control or autonomous elements of surgical procedures. The proliferation of AI-based technologies in static imaging in clinical ophthalmology, continued refinement of AI tools designed for video-based applications, and development of AI-based digital tools in allied surgical fields suggest that ophthalmic surgery is poised for the integration of AI into our microsurgical paradigm.

Moving objects detection based on histogram of oriented gradient algorithm chip for hazy environment

<span>The most important aspects of computer vision are moving object detection (MOD) and tracking. Many signal-processing applications use regional image statistics. Compute-intensive video and image processing with low latency and high throughput is done with field programmable gate array (FPGA) image processing. Local image statistics are used for edge identification and filtering. The histogram of oriented gradients (HoG) algorithm extracts local shape characteristics by equalizing histograms. The objective of the work is to design the hardware chip of the algorithm and perform the simulation in the Xilinx ISE 14.7 simulation environment. The performance of the chip is evaluated in Modelsim 10.0 simulation software to check its feasibility. The performance of the chip design is estimated on Viretx-5 FPGA and compared with the MATLAB-2020 image processing tool-based response time. This form of tracking typically deals with identifying, anchoring, and tracking images and videos. A mask made from a cut-out of the object can then determine the plane's coordinates depending on its position. This type of object tracking is frequently utilized in the field of augmented reality (AR). The algorithm is most suited for object detection using hardware controllers in haze and foggy environments.</span>

Sound source locations and their roles in Japanese voiceless "glottal" fricative production.

Although [h] is described as a glottal fricative, it has never been demonstrated whether [h] has its source exclusively at the glottis. In this study, sound source locations and their influence on sound amplitudes were investigated by conducting mechanical experiments and airflow simulations. Vocal tract data of [h] were obtained in three phonemic contexts from two native Japanese subjects using three-dimensional static magnetic resonance imaging (MRI). Acrylic vocal tract replicas were constructed, and the sound was reproduced by supplying airflow to the vocal tracts with adducted or abducted vocal folds. The sound source locations were estimated by solving the Navier-Stokes equations. The results showed that the amplitudes of sounds produced by the vocal tracts with an open glottis were in a similar range (±3 dB) to those with a glottal gap of 3 mm in some contexts. The sound sources in these cases were observed in the pharyngeal cavity or near the soft palate. Similar degrees of oral constrictions were observed in the real-time MRI, indicating that the sound traditionally described as [h] is produced, at least in some contexts, with sound sources of turbulent flow generated by a supralaryngeal constriction of the following vowel.

Assessment of post-pyeloplasty renal drainage in antenatally detected hydronephrosis by 99mTc-L, L-Ethylenedicysteine renal scintigraphy: the importance of delayed imaging.

Diuretic renal scintigraphy is important in diagnosing pelvi-ureteric junction obstruction (PUJO) in antenatally detected hydronephrotic (ANH) kidneys. Early-phase dynamic renal scintigraphy has several pitfalls contributing to the false interpretation of obstructed drainage, especially after pyeloplasty. This study explores the utility of delayed imaging in 99mTc-L,L-Ethylenedicysteine (EC) diuretic renal scintigraphy to assess post-pyeloplasty renal drainage in ANH. Data from May 2019 to January 2024 was retrospectively studied to identify infants with ANH who underwent surgery for PUJO and pre-and post-surgical assessment of renal drainage using 99mTc-L,L-EC diuretic renal scintigraphy. Dynamic and post-void static images were analyzed to calculate percentage drainage till 3h. Pre- and post-operative quantitative parameters were compared. Receiver operator curve analysis was done to calculate the threshold drainage to detect renal obstruction on postvoid images. In a cohort of 104 patients with a mean age of 10.1 ± 6.5months (range 2-36months) at surgery, 106 renal units (bilateral involvement in two patients) were analyzed. There was no significant difference in the sum of obstructive and equivocal curve patterns (105 vs 79, p = 0.06) and T1/2 values (105 vs 82, p = 0.093) before and after surgery. However, there was a significant difference between the pre-and post-surgery median 3-h percentage drainage (26 vs 80%, p < 0.001). A drainage threshold of less than 59% at 3h had 93.4% sensitivity and 92.5% specificity to detect obstructive drainage. Delayed images in diuretic renal scintigraphy are crucial in accurately interpreting post-pyeloplasty drainage patterns and help overcome pitfalls of the dynamic study.

Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors

Reconstructing images from the Event Horizon Telescope (EHT) observations of M87*, the supermassive black hole at the center of the galaxy M87, depends on a prior to impose desired image statistics. However, given the impossibility of directly observing black holes, there is no clear choice for a prior. We present a framework for flexibly designing a range of priors, each bringing different biases to the image reconstruction. These priors can be weak (e.g., impose only basic natural-image statistics) or strong (e.g., impose assumptions of black hole structure). Our framework uses Bayesian inference with score-based priors, which are data-driven priors arising from a deep generative model that can learn complicated image distributions. Using our Bayesian imaging approach with sophisticated data-driven priors, we can assess how visual features and uncertainty of reconstructed images change depending on the prior. In addition to simulated data, we image the real EHT M87* data and discuss how recovered features are influenced by the choice of prior.

Influence of Age, Gender and BMI on Normal Abdominal Aorta Diameter taken on Abdominal Sonography in Healthy Asymptomatic Pakistani Population

Objective: To evaluate the abdominal aorta diameter in asymptomatic Pakistani population to determine the associations between age, gender and BMI and abdominal aortic diameter measured by ultrasonography. Study Design: Case series. Place and Duration of Study: Department of Radiology, Combined Military Hospital, Lahore, Pakistan, from Jun to Dec 2021. Methodology: A total of ninety-four healthy asymptomatic subjects of both genders, between 18-80 years of age, were enrolled for the study. Aortic diameters were measured (inner to inner method) using electronic calipers on static images. The Anteroposterior and Transverse (TR) diameters were measured at three levels: the first at the aortic hiatus, which was directly below the abdominal aortic commencement, the second at the suprarenal (mid-point), and the third at the aortic bifurcation (lower level). Results: Males had significantly larger (p-value&lt;0.001) anteroposterior and transverse abdominal aorta diameters than females, with abdominal aorta diameter values found to be significantly higher (p-value 0.001) in age group of greater than 40 years except anteroposterior distal abdominal aorta diameter. Similarly, a significant difference (p-value &lt;0.001) was noted in abdominal aorta diameter among patients with different BMI groups other than distal abdominal aorta diameter. Conclusion: Abdominal aorta diameters vary greatly depending on age, gender and BMI. Clinicians must know the usual diameter of the abdominal aorta in order to recognize an aneurysm at an early stage.

Predictive pixel-wise optical encoding: towards single-shot high dynamic range moving object recognition

Conventional low dynamic range (LDR) imaging devices fail to preserve much information for further vision tasks because of the saturation effect. Thus, high dynamic range (HDR) imaging is an important imaging technology in extreme illuminance conditions, which enables a wide range of applications, including photography, autonomous driving, and robotics. Mainstream approaches require multi-shot methods because the conventional camera can only control the exposure globally. Although they perform well on static HDR imaging, they face a challenge with real-time HDR imaging for motional scenes because of the artifact and time latency caused by multi-shot and post-processing. To this end, we propose a framework, termed POE-VP, which achieves single-shot HDR imaging via a pixel-wise optical encoder driven by video prediction. We use highlighted motional license plate recognition as a downstream vision task to demonstrate the performance of POE-VP. From the results of simulation and real scene experiments, we validate that POE-VP outperforms conventional LDR cameras by more than 5 times in recognition accuracy and by more than 200% in information entropy. The dynamic range could reach 120 dB, and the captured data size is verified to be lower than mainstream multi-shot methods by 67%. The running time of POE-VP is also validated to satisfy the needs of high-speed HDR imaging.

Preoperative Immersive Virtual Reality (iVR) Applied to Percutaneous Nephrolithotomy: A Prospective Randomized Clinical Study of Surgical Planning and Clinical Outcomes.

Percutaneous nephrolithotomy (PCNL) is the procedure of choice for the management of complex or large renal stones. A major challenge for the surgeon, however, is the need to assimilate the nearly 2000 static images from a CT scan into a functional mental image to enable surgical planning. Accordingly, we investigated the potential of immersive virtual reality (iVR) to enhance surgical planning and its impact on the outcomes among patients undergoing PCNL. Between 2019-2023, 175 patients undergoing PCNL were pre-operatively randomized into a CT-only group (N=89) or a CT+iVR group (N=86). CT scans were rendered into iVR models that allowed the surgeon not only to visualize and manipulate each patient's relevant anatomy, but also simulate the percutaneous approach to the proposed calyx. Post-operative CT scans were defined as absolute stone-free, <2mm remnants or 2.1-4mm remnants. Pre-operative visualization of the iVR model resulted in a changed calyx of entry in 30% of cases. The CT+iVR group had a significant improvement in absolute stone-free rate (33.70% vs. 20.22%, p=0.043) and overall <4mm remnant rate (62.79% vs. 48.20%, p=0.044). Clavien-Dindo II+IIIa complications were less in the iVR group (3.48% vs. 12.30%, p=0.03). The results were independent of the surgeon's years of PCNL experience. Pre-operative iVR model visualization benefited surgeons and patients alike. From a surgical standpoint, viewing the iVR model resulted in a safer, more effective percutaneous stone removal procedure.

E Pur Si Move! Motion-Based Illusions, Perception and Depiction

ABSTRACT Can static pictures depict motion and temporal properties? This is an open question that is becoming increasingly discussed in both aesthetics and the philosophy of mind. Theorists working on this issue have mainly focused on static pictures of dynamic scenes and streaky images—such as futurists’ paintings or long-exposure photographs. And yet, we could ask: if there is some success in creating an illusory impression of movement in a static image—as is the case in optical illusions of movement, such as Bridget Riley’s Fall (1963: Tate, London), or Kitaoka’s Rotating Snakes Illusion—is this to say that such static images depict movement? As far as I know, no one working on the depiction of motion has specifically and systematically tackled motion-based illusions nor tried to answer this question. This paper considers two cases of optical illusions of movement and concludes that one of them is involved in the depiction of movement. While the declared goal of my analysis is to answer a quite circumscribed question, it is also the occasion to tackle motion-based illusions tout court—to account for the complex visual experiences they elicit and related phenomenology. Moreover, this account has interesting consequences for theorizing depiction and pictorial experience in general. In particular, it constitutes a counterexample to resemblance theories of depiction.

Kinetic Analysis and Metabolism of Poly(Adenosine Diphosphate-Ribose) Polymerase-1-Targeted 18F-Fluorthanatrace PET in Breast Cancer.

The poly(adenosine diphosphate-ribose) polymerase inhibitors (PARPi) have demonstrated efficacy in ovarian, breast, and prostate cancers, but current biomarkers do not consistently predict clinical benefit. 18F-fluorthanatrace (18F-FTT) is an analog to rucaparib, a clinically approved PARPi, and is a candidate biomarker for PARPi response. This study intends to characterize 18F-FTT pharmacokinetics in breast cancer and optimize image timing for clinical trials. A secondary aim is to determine whether 18F-FTT uptake in breast cancer correlates with matched frozen surgical specimens as a reference standard for PARP-1 protein. Methods: Thirty prospectively enrolled women with a new diagnosis of breast cancer were injected with 18F-FTT and imaged dynamically 0-60 min after injection over the chest, with an optional static scan over multiple bed positions starting around 70 min. Kinetic analysis of lesion uptake was performed using blood-pool activity with population radiometabolite corrections. Normal breast and normal muscle reference tissue models were compared with PARP-1 protein expression in 10 patients with available tissue. Plasma radiometabolite concentrations and uptake in tumor and normal muscle were investigated in mouse xenografts. Results: Pharmacokinetics of 18F-FTT were well fit by Logan plot reference region models of reversible binding. However, fits of 2-tissue compartment models assuming negligible metabolite uptake were unstable. Rapid metabolism of 18F-FTT was demonstrated in mice, and similar uptake of radiometabolites was found in tumor xenografts and normal muscle. Tumor 18F-FTT distribution volume ratios relative to normal muscle reference tissue correlated with tissue PARP-1 expression (P < 0.02, n = 10). The tumor-to-normal muscle ratio from a 5-min frame between 50 and 60 min after injection, a potential static scan protocol, closely corresponded to the distribution volume ratio relative to normal muscle and correlated to PARP-1 expression (P < 0.02, n = 10). Conclusion: This study of PARPi analog 18F-FTT showed that uptake kinetics invivo corresponded to expression of PARP-1 and that 18F-FTT quantitation is influenced by radiometabolites that are increasingly present late after injection. Radiometabolites can be controlled by using optimal image acquisition timing or normal muscle reference tissue modeling in dynamic imaging or a tumor-to-normal muscle ratio. Optimal image timing for tumor-to-normal muscle quantification in humans appears to be between 50 and 60 min after injection. Therefore, a clinically practical static imaging protocol commencing 45-55 min after injection may sufficiently balance 18F-FTT uptake with background clearance and radiometabolite interference for quantitative interpretation of PARP-1 expression invivo.

ZnO Nanowire Cold Cathode Hemispherical X‐Ray Sources

AbstractCurved or spherical X‐ray sources are significant for use in intraoperative radiotherapy, adaptive static medical imaging, and high‐throughput industrial inspection, but they are hard to achieve using traditional thermionic cathode point electron sources. In this study, copper (Cu)‐doped zinc oxide (ZnO) nanowires grown on a brass substrate with a designed shape are proposed to achieve cold cathode hemispherical X‐ray sources. The strain‐driven solid–liquid growth model of Cu‐doped ZnO nanowires is proposed, and the oxidation temperature‐dependent and time‐dependent growth characteristics are investigated to optimize the morphologies of ZnO nanowire cold cathodes with a typical turn‐on field of 7.36 MV m−1, a maximum current of 12.54 mA (4.93 mA cm−2) and a uniform field emission image with an area of 2.54 cm2. Hemispherical X‐ray sources formed by Cu‐doped ZnO nanowire field emitters grown on spherical brass alloy and an Al thin film transmission anode target deposited on a hemispherical quartz glass are successfully fabricated, achieving an operating voltage of 39 kV, a dose rate of 240 µGyair s−1 and a projection X‐ray imaging resolution of 2.8 lp mm−1, demonstrating their promising use in a variety of applications.

Radiographic Indicators of Craniocervical Instability: Analyzing Variance of Normative Supine and Upright Imaging in a Healthy Population.

Single-institution retrospective review. To establish baseline ranges and variability of 7 radiographic measurements of the cervical spine in a healthy patient population as potential diagnostic tools for craniocervical instability. Craniocervical instability, common in patients with connective tissue disease such as Ehlers-Danlos Syndrome, often presents with a wide range of symptoms, including neck pain. Current diagnostic methods employ a range of clinical and radiographic features, but diagnostic challenges remain due to missed indications on static imaging and a lack of standardized measurement values and normalized variance. Seventy-two healthy patients with cervical imaging were analyzed. Surgimap software was used to annotate supine computed tomography images, flexion, extension, and neutral x-ray images for measurement. These measurements included the atlanto-dental interval, clival-axial angle, basion-dens interval, basion-axis interval, perpendicular basion to the inferior aspect of C2, also known as Grabb Oakes measurement, and the hard palate to C1 and hard palate to C2. Statistical analysis assessed differences among imaging modalities, and coefficients of variation were calculated for each measurement. Our cohort consisted of a total of 72 patients with a mean age of 64 (SD: 13.54). All measurements except for the basion-axial interval and atlanto-dental interval demonstrated a significant difference between extension and flexion x-ray measurements. clivo-axial angle, hard palate to C1, and hard palate to C2 demonstrated the lowest coefficients of variance across imaging modalities. Understanding normal variance in cervical measurements is invaluable for accurate CCI diagnosis. Using a cohort of healthy patients, this study delineates the distribution and spread of 7 cervical measurements, delineating reference values and variability in these key measurements and highlighting their potential for use as imaging markers for CCI. Level III.

Retraction Note: Three-dimensional face reconstruction of static images and computer standardization issues

Retraction Note: Three-dimensional face reconstruction of static images and computer standardization issues

An Investigation of Metaphoric Perceptions about the Concept of Creative Drama

Purpose: The purpose of this study is to determine whether the perceptions of the participants selected from English teachers about creative drama reflect the general characteristics of creative drama by using metaphor method. Design/Methodology/Approach: Phenomenological research is concerned with how people experience the world at a given time and in a specific context. In other words, phenomenological research aims to describe, understand and interpret the structure of phenomena arising in mind as a result of the interaction of the individuals with the World. “A metaphor form” was used as the data collection tool to determine the perceptions of the teachers about the concept of creative drama. In the form, there is an expression “ creative drama is (a)... because.....”. the participant selection was based on purposive sampling and particiapants were sixty English teacher. Findings: The obtained data were analyzed through content analysis. Results showed that there occured 30 metaphoric expressions and 7 categories. These metaphors were based on game, roleplaying, several themes, creativity, real life, its developmental aspect and wasting time. Highlights: Metaphors direct, shed light and guide our practices. This situation translates into “If a picture is worth a thousand words, a metaphor is worth a thousand pictures; Because a picture just presents a static image, a metaphor provides a mental framework for being about a phenomenon.” (Shuell, 1990) is also clearly reflected. This quote effectively reveals how metaphors are a powerful tool in recording and indicating the general distribution of the human profile and especially the educators themselves.

Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics.

The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this SpecialReport. The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain-relevant assessments via the analysis of relevant imagestatistics. As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis. To create the training dataset, an established 3D virtual breast phantom was adapted. The resulting dataset comprised about 108000 images of size 512 512. For the evaluation of submissions to the Challenge, an ensemble of 10000 DGM-generated images from each submission was employed. The evaluation procedure consisted of two stages. In the first stage, a preliminary check for memorization and image quality (via the Fréchet Inception Distance [FID]) was performed. Submissions that passed the first stage were then evaluated for the reproducibility of image statistics corresponding to several feature families including texture, morphology, image moments, fractal statistics, and skeleton statistics. A summary measure in this feature space was employed to rank the submissions. Additional analyses of submissions was performed to assess DGM performance specific to individual feature families, the four classes in the training data, and also to identify various artifacts. Fifty-eight submissions from 12 unique users were received for this Challenge. Out of these 12 submissions, 9 submissions passed the first stage of evaluation and were eligible for ranking. The top-ranked submission employed a conditional latent diffusion model, whereas the joint runners-up employed a generative adversarial network, followed by another network for image superresolution. In general, we observed that the overall ranking of the top 9 submissions according to our evaluation method (i) did not match the FID-based ranking, and (ii) differed with respect to individual feature families. Another important finding from our additional analyses was that different DGMs demonstrated similar kinds ofartifacts. This Grand Challenge highlighted the need for domain-specific evaluation to further DGM design as well as deployment. It also demonstrated that the specification of a DGM may differ depending on its intendeduse.

What am I looking at? Graduate student accuracy in identification of anatomic structures/landmarks on swallow imaging.

Speech-language pathologists need to accurately identify structures/landmarks on swallow imaging. Foundational learning begins in graduate training. This study aimed to determine graduate student accuracy at identifying anatomical structures/landmarks during swallow evaluations and to determine if accuracy was predicted by type of imaging, anatomical structure, case type (i.e., normal/abnormal). Researchers recruited first-year graduate speech-language pathology students. Each participant reviewed five static images from lateral radiographic swallow studies and five static images from endoscopic swallow studies across 10 cases. Participants identified key anatomic structures and landmarks by clicking on the structure/landmark within a web-based platform. Two experienced speech-language pathologists reviewed and coded participant responses for accuracy. Sixteen graduate speech-language pathology students participated in a within-subjects design. Overall participant accuracy in identification of structure/landmarks was 69% (range 46%-88%). Binomial logistic regression was performed to study the effects of anatomical structure, case type (i.e., normal/abnormal), and image type on likelihood of participant accuracy in identifying anatomical structures (X2(4) = 143.65, p < 0.001). Only anatomical structure was statistically significant (X2(4) = 187.729, p < 0.001). The model explained 23.2% (Nagelkerke's R squared) of the variance in accuracy and correctly classified 78.4% of cases. Sensitivity was 92.1%, specificity was 47.3%, positive predictive value was 79.84%, and negative predictive value was 72.50%. The area under the ROC curve was 0.754, 95% CI [0.716, 0.791]. Graduate student's ability to correctly identify structures/landmarks overall was lower than desired and accuracy varied per structure. Results have implications for improving graduate student training for identification of structures/landmarks on swallow imaging.

Erosion of the temporal bone by vestibular schwannoma: morphometrics and predictive modeling.

To perform a comprehensive morphometric analysis of vestibular schwannomas (VS) using multimodal imaging, focusing on the relationship between tumor characteristics and internal acoustic canal (IAC) changes. We analyzed a cohort of patients undergoing radiosurgery for VS, utilizing high-definition MRI and bone CT for detailed anatomical assessment. Image co-registration and fusion techniques were employed to examine VS and IAC dimensions. Advanced statistical methods, including logistic regression, were applied to identify patterns of IAC dilation and establish predictive indicators for these morphological changes. The study included 659 patients (51.1% female, mean age 56.37years) with evenly distributed tumor lateralization. Koos grades were I (22.9%), II (29.9%), III (38.2%), IVa (8.9%), and IVb (0.3%). Most tumors (90.9%) extended both inside and outside the IAC. Ipsilateral IAC (IIAC) dimensions were significantly larger than contralateral, with IIAC volume 49% greater (p < .0001). Higher Koos grades correlated with increased intra-canalicular lesion volume (icLV), which was strongly associated with IIAC size. Logistic regression identified icLV as the strongest predictor of IIAC dilation (AUC = 0.7674, threshold = 137.52 mm3). The icLV appears central to the pathophysiological development of VS and its impact on IAC anatomy. While limited by a selective patient base and static imaging data, these findings enhance the understanding of VS-IAC interactions, offering insights for improved clinical management and further research.