Computerized classification method for significant coronary artery stenosis on whole-heart coronary MRA using 3D convolutional neural networks with attention mechanisms.

This study aims to develop a computerized classification method for significant coronary artery stenosis on whole-heart coronary magnetic resonance angiography (WHCMRA) images using a 3D convolutional neural network (3D-CNN) with attention mechanisms. The dataset included 951 segments from WHCMRA images of 75 patients who underwent both WHCMRA and invasive coronary angiography (ICA). Forty-two segments with significant stenosis (luminal diameter reduction 75%) on ICA were annotated on WHCMRA images by an experienced radiologist, whereas 909 segments without it were annotated at representative sites.

Evaluating correlations between reading ability and psychophysical measurements of dynamic visual information processing in Japanese adults.

The reading ability of English readers has been shown to correlate with psychophysical measurements of dynamic visual information processing. This study investigated the relationship between reading ability and dynamic visual information processing in healthy adult native Japanese readers (n = 46). Reading ability was assessed using three different tests: the Japanese Adult Reading Test (JART), transposed-letter detection task, and oral reading.

Anomaly detection scheme for lung CT images using vector quantized variational auto-encoder with support vector data description.

This study aims to develop an anomaly-detection scheme for lesions in CT images. Our database consists of lung CT images obtained from 1500 examinees. It includes 1200 normal and 300 abnormal cases.

Washout-parametric imaging with Sonazoid for enhanced differentiation of focal liver lesions.

Purpose: The study aimed to compare the diagnostic performance of washout-parametric imaging (WOPI) with that of conventional contrast-enhanced ultrasound (cCEUS) in differentiating focal liver lesions (FLLs).

Methods: A total of 181 FLLs were imaged with contrast-enhanced ultrasound using Sonazoid, and the recordings were captured for 10 minutes in a prospective setting. WOPI was constructed from three images, depicting the arterial phase (peak enhancement), the early portal venous phase (1-minute post-injection), and the vasculo-Kupffer phase (5 or 10 minutes post-injection).

A Combination of Amide Proton Transfer, Tumor Blood Flow, and Apparent Diffusion Coefficient Histogram Analysis Is Useful for Differentiating Malignant from Benign Intracranial Tumors in Young Patients: A Preliminary Study.

Purpose: To evaluate the amide proton transfer (APT), tumor blood flow (TBF), and apparent diffusion coefficient (ADC) combined diagnostic value for differentiating intracranial malignant tumors (MTs) from benign tumors (BTs) in young patients, as defined by the 2021 World Health Organization classification of central nervous system tumors.

Methods: Fifteen patients with intracranial MTs and 10 patients with BTs aged 0-30 years underwent MRI with APT, pseudocontinuous arterial spin labeling (pCASL), and diffusion-weighted imaging. All tumors were evaluated through the use of histogram analysis and the Mann-Whitney U test to compare 10 parameters for each sequence between the groups.

Aftereffect of perceived motion trajectories.

If our visual system has a distinct computational process for motion trajectories, such a process may minimize redundancy and emphasize variation in object trajectories by adapting to the current statistics. Our experiments show that after adaptation to multiple objects traveling along trajectories with a common tilt, the trajectory of an object was perceived as tilting on the repulsive side. This trajectory aftereffect occurred irrespective of whether the tilt of the adapting stimulus was physical or an illusion from motion-induced position shifts and did not differ in size across the physical and illusory conditions.

Computerized Segmentation Method for Nonmasses on Breast DCE-MRI Images Using ResUNet++ with Slice Sequence Learning and Cross-Phase Convolution.

The purpose of this study was to develop a computerized segmentation method for nonmasses using ResUNet++ with a slice sequence learning and cross-phase convolution to analyze temporal information in breast dynamic contrast material-enhanced magnetic resonance imaging (DCE-MRI) images. The dataset consisted of a series of DCE-MRI examinations from 54 patients, each containing three-phase images, which included one image that was acquired before contrast injection and two images that were acquired after contrast injection. In the proposed method, the region of interest (ROI) slice images are first extracted from each phase image.

Potential Usefulness a Coronal View using an Automated Breast Ultrasound System in Detecting Breast Lesions.

Objective: An automated breast ultrasound system (ABUS) combined with screening mammography has increased cancer detection rates; however, supplemental ABUS use has increased recall rates. In this study, we aimed to identify an accurate and efficient method of ABUS interpretation and evaluate the potential usefulness of its coronal view versus the conventional transverse view.

Materials And Methods: This retrospective observer study included comprised 114 ABUS cases (40 normal, 35 benign, 39 malignant).

Theoretical and Technical Issues Concerning the Measurement of Alpha Frequency and the Application of Signal Detection Theory: Comment on Buergers and Noppeney (2022).

Classical and recent evidence has suggested that alpha oscillations play a critical role in temporally discriminating or binding successively presented items. Challenging this view, Buergers and Noppeney [Buergers, S., & Noppeney, U.

Building a decoder of perceptual decisions from microsaccades and pupil size.

Many studies have reported neural correlates of visual awareness across several brain regions, including the sensory, parietal, and frontal areas. In most of these studies, participants were instructed to explicitly report their perceptual experience through a button press or verbal report. It is conceivable, however, that explicit reporting itself may trigger specific neural responses that can confound the direct examination of the neural correlates of visual awareness.

Pseudocontinuous Arterial Spin Labeling: Clinical Applications and Usefulness in Head and Neck Entities.

As functional magnetic resonance imaging, arterial spin labeling (ASL) techniques have been developed to provide quantitative tissue blood flow measurements, which can improve the performance of lesion diagnosis. ASL does not require contrast agents, thus, it can be applied to a variety of patients regardless of renal impairments and contrast agent allergic reactions. The clinical implementation of head and neck lesions is limited, although, in recent years, ASL has been increasingly utilized in brain lesions.

Tooth detection for each tooth type by application of faster R-CNNs to divided analysis areas of dental panoramic X-ray images.

This study aimed to propose a computerized method for detecting the tooth region for each tooth type as the initial stage in the development of a computer-aided diagnosis (CAD) scheme for dental panoramic X-ray images. Our database consists of 160 panoramic dental X-ray images obtained from 160 adult patients. To reduce false positives (FPs), the proposed method first extracts a rectangular area including all teeth from a dental panoramic X-ray image with a faster region using a convolutional neural network (Faster R-CNN).

Semiautomated Segmentation and Volume Measurements of Cervical Carotid High-Signal Plaques Using 3D Turbo Spin-Echo T1-Weighted Black-Blood Vessel Wall Imaging: A Preliminary Study.

Unstable carotid plaques are visualized as high-signal plaques (HSPs) on 3D turbo spin-echo T1-weighted black-blood vessel wall imaging (3D TSE T1-BB VWI). The purpose of this study was to compare manual segmentation and semiautomated segmentation for the quantification of carotid HSPs using 3D TSE T1-BB VWI. Twenty cervical carotid plaque lesions in 19 patients with a plaque contrast ratio of > 1.

Tumor blood flow and apparent diffusion coefficient histogram analysis for differentiating malignant salivary tumors from pleomorphic adenomas and Warthin's tumors.

We aimed to assess the combined diagnostic value of apparent diffusion coefficient (ADC) and tumor blood flow (TBF) obtained by pseudocontinuous arterial spin labeling (pCASL) for differentiating malignant tumors (MTs) in salivary glands from pleomorphic adenomas (PAs) and Warthin's tumors (WTs). We used pCASL imaging and ADC map to evaluate 65 patients, including 16 with MT, 30 with PA, and 19 with WT. We evaluated all tumors by histogram analyses and compared various characteristics by one-way analysis of variance followed by Tukey post-hoc tests.

A dynamic noise background reveals perceptual motion extrapolation: The twinkle-goes illusion.

We find that on a dynamic noise background, the perceived disappearance location of a moving object is shifted in the direction of motion. This "twinkle-goes" illusion does not require luminance- or chromaticity-based confusability of the object with the background, or on the amount of background motion energy in the same direction as the object motion. This suggests that the illusion is enabled by the dynamic noise masking the offset transients that otherwise accompany an object's disappearance.

A novel strategy to develop deep learning for image super-resolution using original ultra-high-resolution computed tomography images of lung as training dataset.

Purpose: To improve the image quality of inflated fixed cadaveric human lungs by utilizing ultra-high-resolution computed tomography (U-HRCT) as a training dataset for super-resolution processing using deep learning (SR-DL).

Materials And Methods: Image data of nine cadaveric human lungs were acquired using U-HRCT. Three different matrix images of U-HRCT images were obtained with two acquisition modes: normal mode (512-matrix image) and super-high-resolution mode (1024- and 2048-matrix image).

Evaluation of placental oxygenation index using blood oxygen level-dependent magnetic resonance imaging (BOLD-MRI) during normal late pregnancy.

Aim: Noninvasive blood oxygen level-dependent magnetic resonance imaging (BOLD-MRI) has recently been used to evaluate placental oxygenation. However, this method still has unresolved problems, such as long testing times and lack of normal values set. In the present study, we used a shorter protocol in BOLD-MRI and established normal values for placental oxygenation in late pregnancy.

Segmentation of teeth in panoramic dental X-ray images using U-Net with a loss function weighted on the tooth edge.

Panoramic dental X-ray imaging is an established method for the diagnosis of dental problems. However, the resolution of panoramic dental X-ray images is relatively low. Thus, early lesions are often overlooked.

Computer-Aided Diagnosis Scheme for Distinguishing Between Benign and Malignant Masses on Breast DCE-MRI Images Using Deep Convolutional Neural Network with Bayesian Optimization.

Although magnetic resonance imaging (MRI) has a higher sensitivity of early breast cancer than mammography, the specificity is lower. The purpose of this study was to develop a computer-aided diagnosis (CAD) scheme for distinguishing between benign and malignant breast masses on dynamic contrast material-enhanced MRI (DCE-MRI) by using a deep convolutional neural network (DCNN) with Bayesian optimization. Our database consisted of 56 DCE-MRI examinations for 56 patients, each of which contained five sequential phase images.

Attention updates the perceived position of moving objects.

The information used by conscious perception may differ from that which drives certain actions. A dramatic illusion caused by an object's internal texture motion has been put forward as one example. The motion causes an illusory position shift that accumulates over seconds into a large effect, but targeting of the grating for a saccade (a rapid eye movement) is not affected by this illusion.

Diagnostic performance of coronal view in comparison with transverse view of three-dimensional automated breast ultrasound.

Background: Automated breast ultrasound (ABUS) is one of the first ultrasound devices which enables the de-coupling of image acquisition and interpretation. Another feature of ABUS is the coronal view, utilizing three-dimensional volume data reconstructed from two-dimensional transverse images acquired automatically.

Purpose: To assess the diagnostic performance of coronal view interpretation by comparing it with that of the transverse view.

Usefulness of dictionary learning-based processing for improving image quality of sub-millisievert low-dose chest CT: initial experience.

Purpose: To develop a dictionary learning (DL)-based processing technique for improving the image quality of sub-millisievert chest computed tomography (CT).

Materials And Methods: Standard-dose and sub-millisievert chest CT were acquired in 12 patients. Dictionaries including standard- and low-dose image patches were generated from the CT datasets.

Improving Image Resolution of Whole-Heart Coronary MRA Using Convolutional Neural Network.

Whole-heart coronary magnetic resonance angiography (WHCMRA) permits the noninvasive assessment of coronary artery disease without radiation exposure. However, the image resolution of WHCMRA is limited. Recently, convolutional neural networks (CNNs) have obtained increased interest as a method for improving the resolution of medical images.