A review of automatic liver tumor segmentation based on computed tomography / 生物医学工程学杂志

Liver cancer is a common type of malignant tumor in digestive system. At present, computed tomography (CT) plays an important role in the diagnosis and treatment of liver cancer. Segmentation of tumor lesions based on CT is thus critical in clinical diagnosis and treatment. Due to the limitations of manual segmentation, such as inefficiency and subjectivity, the automatic and accurate segmentation based on advanced computational techniques is becoming more and more popular. In this review, we summarize the research progress of automatic segmentation of liver cancer lesions based on CT scans. By comparing and analyzing the results of experiments, this review evaluate various methods objectively, so that researchers in related fields can better understand the current research progress of liver cancer segmentation based on CT scans.

Progresses of MRI in assessment of temporal lobe epilepsy / 中国介入影像与治疗学

Temporal lobe epilepsy (TLE) is the most common clinical type of epilepsy,which is generally available for drug therapy.Surgical operation will be considered when patients developing into refractory epilepsy.Currently,treatment response evaluation is based on the observation of seizure remission in a certain period,and the real-time and objective evaluation is unavailable.With the improvement of MRI technology and image analysis methods,the multimodal MRI has been widely used to assess the effectiveness of TLE treatment.The progresses of multi-modal MRI and its new technique in assessment of epilepsy remission and cognitive function in TLE patients were reviewed in this article.

The computer-aided diagnosis of attention-deficit hyperactivity disorder and autism spectrum disorder based on structural magnetic resonance imaging / 中华行为医学与脑科学杂志

Child and adolescent mental disorders are common disorders with various symptoms,and attracting more attention due to the increasing prevalence.Mental disorders,especially the attention-deficit hyperactivity disorder (ADHD) and the autism spectrum disorder (ASD),have great influence on the development of children and adolescents.Nowadays,the biomarkers from neuroimaging such as magnetic resonance imaging (MRI) have a great importance on the diagnosis of mental disorders,and machine learning has been proved to be very powerful in the processing for neuroimages.Nowadays,many researchers are focusing on the studies of computer-aided diagnosis (CAD) based on machine learning and neuroimaging.In this review,the technical details of machine learning based CAD of child and adolescent mental disorders are briefly introduced,and the research progress in CAD of ADHD and ASD based on machine learning and structural MRI are summarized.These studies showed that many machine learning methods have been used in the diagnosis of child and adolescent mental disorders,but the relevant methods cannot be applied to clinical diagnosis.Further studies should be conducted to improve the diagnostic ability of machine learning methods from multiple perspectives,and provide an objective and reliable tool for the clinical diagnosis of child and adolescent mental disorders.

Effects of Chlamydia pneumoniae infection and hyperlipidemia on the expression of NF-?B and AP-1 in myocardium / 中国病理生理杂志

AIM: To investigate the effects of Chlamydia pneumoniae infection and hyperlipidemia on the expression of NF-?B and AP-1 in the myocardium. METHODS: The indirect immunofluorescence method was used to examine wild C57BL/6J mice infected with Chlamydia pneumoniae and fed with an atherogenic diet. The expression of the subunit of NF-?B, P50, and c-Fos in the murine myocardium was observed. RESULTS: Chlamydia pneumoniae infection and hyperlipidemia induced the activation of NF-?B and AP-1 in murine myocardium. P50 and c-Fos were not detected in the controls, but there were different levels of positive expression in the experiments (P