Postpartum depression (PPD) is a serious postpartum mental health problem worldwide. However, the cortical structural alterations in patients with PPD remain unclear. This study investigated the cortical structural alterations of PPD patients through multidimensional structural patterns and their potential correlations with clinical severity.
High-resolution 3D T1 structural images were acquired from 21 drug-naive patients with PPD and 18 healthy postpartum women matched for age, educational level, and body mass index. The severity of PPD was assessed by using the Hamilton Depression Scale (HAMD) and Edinburgh Postnatal Depression Scale (EPDS) scores. Cortical morphological parameters including cortical thickness, surface area, and mean curvature were calculated using the surface-based morphometric (SBM) method. General linear model (GLM) analyses were performed to evaluate the relationship of cortical morphological parameters with clinical scales.
In the present study, PPD patients showed a thinner cortical thickness in the right inferior parietal lobule compared with the healthy controls. Increased surface area was observed in the left superior frontal gyrus, caudal middle frontal gyrus, middle temporal gyrus, insula, and right supramarginal cortex in PPD patients. Likewise, PPD patients exhibited a higher mean curvature in the left superior and right inferior parietal lobule. Furthermore, increased cortical surface area in the left insula had a positive correlation with EPDS scores, and higher mean curvature in the left superior parietal lobule was negatively correlated with EPDS scores.
First, SBM cannot reflect the changes of subcortical structures that are considered to play a role in the development of PPD. Second, the sample size of this study is small. These positive results should be interpreted with caution. Third, this cross-sectional study does not involve a comparison of structural MRI before and after pregnancy.
The complex cortical structural alterations of patients with PPD mainly involved the prefrontal and parietal regions. The morphometric alterations in these specific regions may provide promising markers for assessing the severity of PPD.

Finger vein (FV) biometrics is one of the most promising individual recognition traits, which has the capabilities of uniqueness, anti-forgery, and bio-assay, etc. However, due to the restricts of imaging environments, the acquired FV images are easily degraded to low-contrast, blur, as well as serious noise disturbance. Therefore, how to extract more efficient and robust features from these low-quality FV images, remains to be addressed. In this paper, a novel feature extraction method of FV images is presented, which combines curvature and radon-like features (RLF). First, an enhanced vein pattern image is obtained by calculating the mean curvature of each pixel in the original FV image. Then, a specific implementation of RLF is developed and performed on the previously obtained vein pattern image, which can effectively aggregate the dispersed spatial information around the vein structures, thus highlight vein patterns and suppress spurious non-boundary responses and noises. Finally, a smoother vein structure image is obtained for subsequent matching and verification. Compared with the existing curvature-based recognition methods, the proposed method can not only preserve the inherent vein patterns, but also eliminate most of the pseudo vein information, so as to restore more smoothing and genuine vein structure information. In order to assess the performance of our proposed RLF-based method, we conducted comprehensive experiments on three public FV databases and a self-built FV database (which contains 37,080 samples that derived from 1030 individuals). The experimental results denoted that RLF-based feature extraction method can obtain more complete and continuous vein patterns, as well as better recognition accuracy.

Amblyopia is generally considered a neurodevelopmental disorder that results from abnormal visual experiences in early childhood and may persist to adulthood. The neural basis of amblyopia has been a matter of interest for many decades, but the critical neural processing sites in amblyopia are not entirely understood. Although many functional neuroimaging studies have found abnormal neuronal responses both within and beyond V1, few studies have focused on the neurophysiologic abnormalities in the visual cortex from the viewpoint of potential structural reorganization. In this study, we used a well-validated and highly accurate surface-based method to examine cortical morphologic changes in the visual cortex using multiple parameters (including cortical thickness, surface area, volume and mean curvature).
The cortical thicknesses of the bilateral V1, left V2, left ventral V3, left V4 and left V5/MT+ in patients were significantly thinner than that in controls. The mean curvature of the bilateral V1 was significantly increased in the patients compared with the controls. For the surface area and gray matter volume, no significant differences were found between patients and controls in all region of interests. The cortical thicknesses of the bilateral V1 were both negatively correlated with the amount of anisometropia. No significant correlations were found between any other surface parameters and clinical variables.
In addition to cortical thickness, the altered mean curvature of the cortex may indicate neuroanatomic impairments of the visual cortex in patients with anisometropic amblyopia. Moreover, the structural changes were bilateral in the primary visual cortex but were unilateral in the secondary and more senior visual cortex.