Effects of audio-visual aids on foreign language test anxiety, reading and listening comprehension, and retention in EFL learners.

This study examined the effects of audio-visual aids on anxiety, comprehension test scores, and retention in reading and listening to short stories in English as a Foreign Language (EFL) classrooms. Reading and listening tests, general and test anxiety, and retention were measured in English-major college students in an experimental group with audio-visual aids (n=83) and a control group without audio-visual aids (n=94) with similar general English proficiency. Lower reading test anxiety, unchanged reading comprehension scores, and better reading short-term and long-term retention after four weeks were evident in the audiovisual group relative to the control group. In addition, lower listening test anxiety, higher listening comprehension scores, and unchanged short-term and long-term retention were found in the audiovisual group relative to the control group after the intervention. Audio-visual aids may help to reduce EFL learners' listening test anxiety and enhance their listening comprehension scores without facilitating retention of such materials. Although audio-visual aids did not increase reading comprehension scores, they helped reduce EFL learners' reading test anxiety and facilitated retention of reading materials.

Cortical shape and curvedness analysis of structural deficits in remitting and non-remitting depression.

In morphometric neuroimaging studies, the relationship between brain structural changes and the antidepressant treatment response in patients with major depressive disorder has been explored to search depression-trait biomarkers. Although patients were treated with serotonin-related drugs, whether the same treatment resulted in remission and non-remission in depressed patients is currently under investigation. We recruited 25 depressed patients and 25 healthy controls and acquired volumetric magnetic resonance imaging of each participant. We used the shape index and curvedness to classify cortical shapes and quantify shape complexities, respectively, in studying the pharmacological effect on brain morphology. The results showed that different regions of structural abnormalities emerged between remitting and non-remitting patients when contrasted with healthy controls. In addition to comparing structural metrics in each cortical parcellation, similar to the traditional voxel-based morphometric method, we highlighted the importance of structural integrity along the serotonin pathway in response to medication treatment. We discovered that disrupted serotonin-related cortical regions might cause non-remission to antidepressant treatment from a pharmacological perspective. The anomalous areas manifested in non-remitting patients were mainly in the frontolimbic areas, which can be used to differentiate remitting from non-remitting participants before medication treatment. Because non-remission is the failure to respond to treatment with serotonin-related drugs, our method may help clinicians choose appropriate medications for non-remitting patients.

Using three-dimensional multigrid-based snake and multiresolution image registration for reconstruction of cranial defect.

In cranioplasty, neurosurgeons use bone grafts to repair skull defects. To ensure the protection of intracranial tissues and recover the original head shape for aesthetic purposes, a custom-made pre-fabricated prosthesis must match the cranial incision as closely as possible. In our previous study (Liao et al. in Med Biol Eng Comput 49:203-211, 2011), we proposed an algorithm consisting of the 2D snake and image registration using the patient's own diagnostic low-resolution and defective high-resolution computed tomography (CT) images to repair the impaired skull. In this study, we developed a 3D multigrid snake and employed multiresolution image registration to improve the computational efficiency. After extracting the defect portion images, we designed an image-trimming process to remove the bumped inner margin that can facilitate the placement of skull implants without manual trimming during surgery. To evaluate the performance of the proposed algorithm, a set of skull phantoms were manufactured to simulate six different conditions of cranial defects, namely, unilateral, bilateral, and cross-midline defects with 20 or 40% skull defects. The overall image processing time in reconstructing the defect portion images can be reduced from 3 h to 20 min, as compared with our previous method. Furthermore, the reconstruction accuracies using the 3D multigrid snake were superior to those using the 2D snake.

Quantifying cerebellar atrophy in multiple system atrophy of the cerebellar type (MSA-C) using three-dimensional gyrification index analysis.

Multiple system atrophy of the cerebellar type (MSA-C) is a degenerative neurological disease of the central nervous system. This study employed a method named, "surface-based three-dimensional gyrification index" (3D-GI) to quantify morphological changes in normal cerebellum (including brainstem) and atrophied cerebellum, in patients with MSA-C. We assessed whether 3D-GI can exclude gender and age differences to quantify cerebellum and brainstem atrophy more accurately. Sixteen healthy subjects and 16 MSA-C patients participated in this study. We compared 3D-GI values and volumes in the cerebellum, based on T1-weighted MR images. We also compared the images of reconstructed 3D cerebellum gray matter (3D-CBGM) and cerebellum white matter (3D-CBWM) to detect the atrophied cerebellar region in MSA-C patients. The 3D-GI values were in a stable range with small variances, exhibiting no gender effect and no age-related shrinkage. Significantly lower 3D-GI values were exhibited in both CBGM and CBWM of the MSA-C patients compared with healthy subjects, even in the early phases of the disease. Decreases in 3D-GI values indicated the degeneration of the cerebellar folding structure, exactly reflecting the morphological changes in cerebellum. The 3D-GI method based on CBGM resulted in superior discriminative accuracy compared with the CBGM volumetric method. Using the two-dimensional 3D-GI values, the K-means classifier can evidently discriminate the MSA-C patients from healthy subjects.

Three-dimensional reconstruction of cranial defect using active contour model and image registration.

In neurosurgery, cranial incisions during craniotomy can be recovered by cranioplasty--a surgical operation using cranial implants to repair skull defects. However, surgeons often encounter difficulties when grafting prefabricated cranial plates into defective areas, since a perfect match to the cranial incision is difficult to achieve. Previous studies using mirroring technique, surface interpolation, or deformed template had limitations in skull reconstruction to match the patient's original appearance. For this study, we utilized low-resolution and high-resolution computed tomography images from the patient to repair skull defects, whilst preserving the original shape. Since the accuracy of skull reconstruction was associated with the partial volume effects in the low-resolution images and the percentage of the skull defect in the high-resolution images, the low-resolution images with intact skull were resampled and thresholded followed by active contour model to suppress partial volume artifacts. The resulting low-resolution images were registered with the high-resolution ones, which exhibited different percentages of cranial defect, to extract the incised cranial part. Finally, mesh smoothing refined the three-dimensional model of the cranial defect. Simulation results indicate that the reconstruction was 93.94% accurate for a 20% skull material removal, and 97.76% accurate for 40% skull material removal. Experimental results demonstrate that the proposed algorithm effectively creates a customized implant, which can readily be used in cranioplasty.

A hybrid strategy to integrate surface-based and mutual-information-based methods for co-registering brain SPECT and MR images.

Co-registration of brain SPECT and MR images has been used extensively in clinical applications. The complementary features of two major co-registration methods--surface- and mutual-information-based (MI-based)--motivated us to study a hybrid-based scheme that uses the surface-based method to achieve a quick alignment, followed by the MI-based method for fine tuning. Computer simulations were conducted to evaluate the accuracy and robustness of surface-, MI-, and hybrid-based registration methods by designing different levels of noise and mismatch in the registration experiments. Results demonstrated that the hybrid surface-MI-based scheme outperforms both the surface- and MI-based methods in providing superior accuracy and success rates. Specifically, the translational and rotational errors were no more than 1 mm and 2°, respectively, with consistent success rates over 98%. Besides, the hybrid-based method saved 12-53% of the computation efforts, compared with using the MI-based method alone. We recommend the use of hybrid-based method when the orientational differences between the floating and reference images exceed 10°.

Cortical complexity analysis of patients with bipolar disorder using three-dimensional gyrification index.

Bipolar disorder (BD) is a common affective disorder. In morphometric brain imaging studies, BD subjects have atrophic gray matter, especially in the prefrontal area. These structural abnormalities could involve the change of cortical shape. Gyrification index (GI) is a useful metric to measure the degree of cortical complexity. This work aims to compare the cortical development between bipolar patients and healthy controls using GI. No significant difference was detected between two groups. However, we found asymmetry pattern of cortical complexity was increased in limbic lobe on bipolar patients. Significant negative correlation was also observed between rating scores and asymmetry coefficients in frontal lobe.

A comparison between the surface-based and mutual-information-based methods for co-registering SPECT and MR images.

Single photon emission computed tomography (SPECT) and magnetic resonance (MR) images are two common modalities in brain imaging society. Co-registration of brain SPECT and MR images has been used extensively in a number of clinical applications. The surface-based method and the mutual-information-based method are two major co-registration methods. The former aligns two volumetric images based on the cost function derived from brain surfaces, whereas the latter matches two volumetric images based on maximizing the mutual information (MI) between intensities of two images. To the best of our knowledge, these two methods have neither been compared, nor conjointly used to register the brain SPECT and MR images. Simulation results show that the surface-based method is more robust to the large deviation of initial guesses and computationally efficient, while the MI-based method provides better precision. The complementary features of these two methods motivated us to propose a hybrid strategy in which the surface-based method is employed to rapidly achieve a rough alignment followed by the MI-based method for fine tuning the results. Results from simulations suggested that only two iterations of MI calculation were required after surface-based registration and thereby lots of computation efforts can be saved.