Selective gene expression profiling contributes to a better understanding of the molecular pathways underlying the histological changes observed after RHMVL.

Background: In previous studies, five vasoactive drugs were investigated for their effect on the recovery process after extended liver resection without observing relevant improvements. We hypothesized that an analysis of gene expression could help to identify potentially druggable pathways and could support the selection of promising drug candidates.

Methods: Liver samples obtained from rats after combined 70% partial hepatectomy and right median hepatic vein ligation (n = 6/group) sacrificed at 0 h, 24 h, 48 h, and 7days were selected for this study.

Semantic Segmentation of Intralobular and Extralobular Tissue from Liver Scaffold H&E Images.

Decellularized tissue is an important source for biological tissue engineering. Evaluation of the quality of decellularized tissue is performed using scanned images of hematoxylin-eosin stained (H&E) tissue sections and is usually dependent on the observer. The first step in creating a tool for the assessment of the quality of the liver scaffold without observer bias is the automatic segmentation of the whole slide image into three classes: the background, intralobular area, and extralobular area.

Novel morphological multi-scale evaluation system for quality assessment of decellularized liver scaffolds.

Decellularized scaffolds can serve as an excellent three-dimensional environment for cell repopulation. They maintain tissue-specific microarchitecture of extracellular matrix proteins with important spatial cues for cell adhesion, migration, growth, and differentiation. However, criteria for quality assessment of the three-dimensional structure of decellularized scaffolds are rather fragmented, usually study-specific, and mostly semi-quantitative.

LEMming: A Linear Error Model to Normalize Parallel Quantitative Real-Time PCR (qPCR) Data as an Alternative to Reference Gene Based Methods.

Background: Gene expression analysis is an essential part of biological and medical investigations. Quantitative real-time PCR (qPCR) is characterized with excellent sensitivity, dynamic range, reproducibility and is still regarded to be the gold standard for quantifying transcripts abundance. Parallelization of qPCR such as by microfluidic Taqman Fluidigm Biomark Platform enables evaluation of multiple transcripts in samples treated under various conditions.

Fast and accurate identification of fat droplets in histological images.

Background And Objective: The accurate identification of fat droplets is a prerequisite for the automatic quantification of steatosis in histological images. A major challenge in this regard is the distinction between clustered fat droplets and vessels or tissue cracks.

Methods: We present a new method for the identification of fat droplets that utilizes adjacency statistics as shape features.

One Size Fits All: Evaluation of the Transferability of a New "Learning" Histologic Image Analysis Application.

Quantitative analysis of histologic slides is of importance for pathology and also to address surgical questions. Recently, a novel application was developed for the automated quantification of whole-slide images. The aim of this study was to test and validate the underlying image analysis algorithm with respect to user friendliness, accuracy, and transferability to different histologic scenarios.

Practical quantification of necrosis in histological whole-slide images.

Since the histological quantification of necrosis is a common task in medical research and practice, we evaluate different image analysis methods for quantifying necrosis in whole-slide images. In a practical usage scenario, we assess the impact of different classification algorithms and feature sets on both accuracy and computation time. We show how a well-chosen combination of multiresolution features and an efficient postprocessing step enables the accurate quantification necrosis in gigapixel images in less than a minute.