NeuralMarker: A Framework for Learning General Marker Correspondence

We tackle the problem of estimating correspondences from a general marker, such as a movie poster, to an image that captures such a marker. Conventionally, this problem is addressed by fitting a homography model based on sparse feature matching. However, they are only able to handle plane-like markers and the sparse features do not sufficiently utilize appearance information. In this paper, we propose a novel framework NeuralMarker, training a neural network estimating dense marker correspondences under various challenging conditions, such as marker deformation, harsh lighting, etc. Besides, we also propose a novel marker correspondence evaluation method circumstancing annotations on real marker-image pairs and create a new benchmark. We show that NeuralMarker significantly outperforms previous methods and enables new interesting applications, including Augmented Reality (AR) and video editing.Comment: Accepted by ToG (SIGGRAPH Asia 2022). Project Page: https://drinkingcoder.github.io/publication/neuralmarker

Clusterin confers gmcitabine resistance in pancreatic cancer

<p>Abstract</p> <p>Objective</p> <p>To measure clusterin expression in pancreatic cancer tissues and cell lines and to evaluate whether clusterin confers resistance to gmcitabine in pancreatic cancer cells.</p> <p>Methods</p> <p>Immunohistochemistry for clusterin was performed on 50 primary pancreatic cancer tissues and 25 matched backgrounds, and clusterin expression in 5 pancreatic cancer cell lines was quantified by Western blot and PT-PCR. The correlation between clusterin expression level and gmcitabine IC50 in pancreatic cancer cell lines was evaluated. The effect of an antisense oligonucleotide (ASO) against clusterin(OGX-011) on gmcitabine resistance was evaluated by MTT assays. Xenograft model was used to demonstrate tumor growth.</p> <p>Results</p> <p>Pancreatic cancer tissues expressed significantly higher levels of clusterin than did normal pancreatic tissues (<it>P </it>< 0.01). Clusterin expression levels were correlated with gmcitabine resistance in pancreatic cancer cell lines, and OGX-011 significantly decreased BxPc-3 cells resistance to gmcitabine (<it>P </it>< 0.01). <it>In vivo </it>systemic administration of AS clusterin and gmcitabine significantly decreased the s.c. BxPC-3 tumor volume compared with mismatch control ODN plus gmcitabine.</p> <p>Conclusion</p> <p>Our finding that clusterin expression was significantly higher in pancreatic cancer than in normal pancreatic tissues suggests that clusterin may confer gmcitabine resistance in pancreatic cancer cells.</p

Data-enabled digestive medicine: a new big data analytics platform

This paper presents a big data analystics platform for clinical research and practice in the Gastroenterology Department of Xiangya Hospital at Central South University in China. This platform features a comprehensive and systematic support of big data in digestive medicine including geneneral health management, clinical gastroenterology practice, and related genomics research, which is proven to be helpful in real world clinical practices. A typical use case of integrated analysis based on electronic medical records and colonoscopy data was presented and discussed, the analaystic report on risk factors of colorectal diseases shows a reasonable recommendation about the age when people should start to screen the colorectal cancer, which could be very useful to individual and group health management for the general population in China