Laryngeal disease classification is a relatively hard task in medical image processing resulting from its complex structures and varying viewpoints in data collection. Some existing methods try to tackle this task via the convolutional neural network, but they more or less ignore the intrinsic difficulty differences among different input samples and suffer from high training complexity. In order to better resolve these problems, an end-to-end Hierarchical Dynamic Convolutional Network (HDCNet) is proposed, which can dynamically process the input samples based on their difficulty. For the easy-classified samples, the HDCNet processes them with a smaller resolution and a relatively small network, while the difficult samples are passed to a large network with a larger resolution for more accurate classification results. Furthermore, a Feature Reuse Module (FRM) is designed to transfer the features learned by the small network to the corresponding block in the deep network to enhance the overall performance of some rather complicated samples. To validate the effectiveness of the proposed HDCNet, comprehensive experiments are conducted on the public available laryngeal disease classification dataset and HDCNet provides superior performances compared with other current state-of-the-art methods.

Doyne honeycomb retinal dystrophy (DHRD)/malattia leventinese (ML) is a rare allelic condition with massive drusen in the posterior fundus caused by EFEMP1 gene mutation. Patients showed decreased vision when the lesion affected the macular area. At present, the treatment efficiency is not satisfactory. In this study, we presented a family with DHRD/ML disease and analyzed the pathological and genetic information. A 28-year-old female patient presented to our department due to impaired visual acuity for 10 years especially in the right eye with deterioration for 5 months. Gene sequencing was performed by MyGenostics (Peking, China). Gene sequencing results revealed heterozygous mutations in EFEMP1 gene, which were consistent with the DHRD/ ML. Single heterozygous mutation (c.1033C > T) was observed in each of the three blood samples. This missense mutation triggered p.R345W. DHRD/ML is a rare disease associated with EFEMP1 gene mutation. Up to now, we are not sure whether these lesions are associated with the onset of DHRD/ML. In future, we hope to find out the exact relationship between them.