Automated classification of healthy and keloidal collagen patterns based on processing of SHG images of human skin

All‐optical microspectroscopic and tomographic tools have a great potential for the clinical investigation of human skin and skin diseases. However, automated optical tomography or even microscopy generate immense data sets. Therefore, in order to implement such diagnostic tools into the medical practice in both hospitals and private practice, there is a need for automated data handling and image analysis ideally implementing automized scores to judge the physiological state of a tissue section. In this contribution, the potential of an image processing algorithm for the automated classification of skin into normal or keloid based on second‐harmonic generation (SHG) microscopic images is demonstrated. Such SHG data is routinely recorded within a multimodal imaging approach. The classification of the tissue implemented in the algorithm employs the geometrical features of collagen patterns that differ depending on the constitution, i.e., physiological status of the skin. (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

基于高光谱成像和主成分分析的水稻茎叶分割

在单株水稻表型测量研究中,为了实现绿叶面积和茎叶相关表型参数的准确计算提供技术保障,茎叶的分割是非常重要的一步。传统的人工测量方法费时费力,且主观性较强,而基于普通相机拍摄的彩色图像进行分割效果很差。本研究介绍了一种使用可见光-近红外高光谱成像系统自动区分单株盆栽水稻茎叶的方法。首先将各波长下的图像从原始二进制数据中提取出来,接着使用主成分分析所有波长下的图像,并提取出主要的主成分图像,再基于数字图像处理技术将茎叶区分开。实验结果表明,本系统以及文中所用方法对分蘖盛期的水稻茎叶有很好的分割效果,这为后续水稻茎叶表型性状高通量、数字化、无损准确提取提供了重要的技术保障,并进一步促进植物表型组学的发展。     

Comparison of photosynthetic damage from arthropod herbivory and pathogen infection in understory hardwood saplings

Arthropods and pathogens damage leaves in natural ecosystems and may reduce photosynthesis at some distance away from directly injured tissue. We quantified the indirect effects of naturally occurring biotic damage on leaf-level photosystem II operating efficiency (Φ_PSII) of 11 understory hardwood tree species using chlorophyll fluorescence and thermal imaging. Maps of fluorescence parameters and leaf temperature were stacked for each leaf and analyzed using a multivariate method adapted from the field of quantitative remote sensing. Two tree species, Quercus velutina and Cercis canadensis, grew in plots exposed to ambient and elevated atmospheric CO₂ and were infected with Phyllosticta fungus, providing a limited opportunity to examine the potential interaction of this element of global change and biotic damage on photosynthesis. Areas surrounding damage had depressed Φ_PSII and increased down-regulation of PSII, and there was no evidence of compensation in the remaining tissue. The depression of Φ_PSII caused by fungal infections and galls extended >2.5 times further from the visible damage and was ∼40% more depressed than chewing damage. Areas of depressed Φ_PSII around fungal infections on oaks growing in elevated CO₂ were more than 5 times larger than those grown in ambient conditions, suggesting that this element of global change may influence the indirect effects of biotic damage on photosynthesis. For a single Q. velutina sapling, the area of reduced Φ_PSII was equal to the total area directly damaged by insects and fungi. Thus, estimates based only on the direct effect of biotic agents may greatly underestimate their actual impact on photosynthesis.     

Medical image registration: a review

This paper presents a review of automated image registration methodologies that have been used in the medical field. The aim of this paper is to be an introduction to the field, provide knowledge on the work that has been developed and to be a suitable reference for those who are looking for registration methods for a specific application. The registration methodologies under review are classified into intensity or feature based. The main steps of these methodologies, the common geometric transformations, the similarity measures and accuracy assessment techniques are introduced and described.