Mask R-CNN Transfer Learning Variants for Multi-Organ Medical Image Segmentation

Medical abdomen image segmentation is a challenging task owing to discernible characteristics of the tumour against other organs. As an effective image segmenter, Mask R-CNN has been employed in many medical imaging applications, e.g. for segmenting nucleus from cytoplasm for leukaemia diagnosis and skin lesion segmentation. Motivated by such existing studies, this research takes advantage of the strengths of Mask R-CNN in leveraging on pre-trained CNN architectures such as ResNet and proposes three variants of Mask R-CNN for multi-organ medical image segmentation. Specifically, we propose three variants of the Mask R-CNN transfer learning model successively, each with a set of configurations modified from the one preceding. To be specific, the three variants are (1) the traditional transfer learning with customized loss functions with comparatively more weightage on the segmentation performance, (2) transfer learning based on Mask R-CNN with deepened re-trained layers instead of only the last two/three layers as in traditional transfer learning, and (3) the fine-tuning of Mask R-CNN with expansion of the Region of Interest pooling sizes. Evaluating using Beyond-the-Cranial-Vault (BTCV) abdominal dataset, a well-established benchmark for multi-organ medical image segmentation, the three proposed variants of Mask R-CNN obtain promising performances. In particular, the empirical results indicate the effectiveness of the proposed adapted loss functions, the deepened transfer learning process, as well as the expansion of the RoI pooling sizes. Such variations account for the great efficiency of the proposed transfer learning variant schemes for undertaking multi-organ image segmentation tasks

Comparative Study on Static Term Structure of Interest Rates

The term structure of interest rates has been a hot topic in the financial sector. With the accelerating process of interest rate liberalization, to seek a representative benchmark interest rate of the market is basis for the fixed income products pricing. This paper using Nelson-Siegel-Svensson model and polynomial spline model fitting analysis is carried out on bond transaction data of Shanghai stock exchange in China, through analysis and comparison of the two models, to choose the appropriate method to fit the term structure of interest rates

Razina industrijskog održivog razvoja u Kini i faktori utjecaja

This research aims to set up a comprehensive index system to evaluate the sustainable development level of the industrial sector in China and to determine the key influencing factors that hinder the sector’s sustainable development. To achieve these research goals, we build a theoretical model with 26 indexes selected from resource, environment, economy, and society subsystems. An empirical analysis is conducted through Principal Component Analysis and Structural Equation Modeling. Results indicate that the sustainable development level of China’s industrial sector became positive in 2007 and peaked in 2012. The environment subsystem has the largest effect on the sustainable development level. The sustainable development level is also greatly influenced by solid wastes, production of non-renewable resources, energy consumption per unit of gross domestic product (GDP), and industrial research and development (R&D) expenditure. The basic conclusion is that the sustainable development level of the industrial sector in China can be enhanced through improving the utilization efficiency of resources, increasing the contribution of technology progress to GDP, and developing renewable resources.Cilj ovog istraživanja je uspostaviti sveobuhvatan indeks sustava za procjenu razine održivog razvoja industrijskog sektora u Kini i odrediti ključne čimbenike koji sprječavaju održivi razvoj tog sektora. Za postizanje ovih znanstvenoistraživačkih ciljeva, izgradili smo model od 26 indeksa odabranih iz resursa, okoliša, gospodarstva i društvenih podsustava. Empirijska analiza provodi se pomoću analize glavnih komponenti i modeliranja strukturnih jednadžbi. Rezultati pokazuju da je razina održivog razvoja kineskog industrijskog sektora postao pozitivan 2007.godine, a vrhunac dosegnuo 2012. godine. Podsustav okoliša ima najveći utjecaj na razinu održivog razvoja. Razina održivog razvoja također je pod velikim utjecajem krutog otpada, proizvodnje neobnovljivih resursa, potrošnje energije po jedinici bruto domaćeg proizvoda (BDP-a) i troškova za industrijsko istraživanje i razvoj. Osnovni zaključak je da se razina održivog razvoja industrijskog sektora u Kini može poboljšati povećanjem učinkovitosti korištenja resursa, većim doprinosom tehnologijskog napretka u BDP-u i razvijanjem obnovljivih resursa

Evaluating the Influence of Spatial Resampling for Motion Correction in Resting-State Functional MRI

Head motion is one of major concerns in current resting-state functional MRI studies. Image realignment including motion estimation and spatial resampling is often applied to achieve rigid-body motion correction. While the accurate estimation of motion parameters has been addressed in most studies, spatial resampling could also produce spurious variance, and lead to unexpected errors on the amplitude of BOLD signal. In this study, two simulation experiments were designed to characterize these variance related with spatial resampling. The fluctuation amplitude of spurious variance was first investigated using a set of simulated images with estimated motion parameters from a real dataset, and regions more likely to be affected by spatial resampling were found around the peripheral regions of the cortex. The other simulation was designed with three typical types of motion parameters to represent different extents of motion. It was found that areas with significant correlation between spurious variance and head motion scattered all over the brain and varied greatly from one motion type to another. In the last part of this study, four popular motion regression approaches were applied respectively and their performance in reducing spurious variance was compared. Among them, Friston 24 and Voxel-specific 12 model (Friston et al., 1996), were found to have the best outcomes. By separating related effects during fMRI analysis, this study provides a better understanding of the characteristics of spatial resampling and the interpretation of motion-BOLD relationship

A Model of Customer Lifetime Value Consider with Word-of-mouth Marketing Value

With the rapid development of IT technology and fierce competition of market, the customer relationship management(CRM) has gained its importance in the market. Companies have attached importance to acquiring and retaining the most profitable customers. So calculating customer’s value is a significant segment for every effective CRM. Many researches have been performed to calculate customer’s value based on customer lifetime value (LTV). But, these calculations can’t effectively include the whole customer value, especially for the word-of-mouth marketing value. This paper proposes a new LTV model which considers the customer’s past profit contribution, potential value and word-of-mouth marketing value, and gives a more reasonable LTV value in CRM for the company to make a decision