In our image segmentation pipeline, we use FCNs to obtain normalized images, which are then iteratively refined by means of a FC-ResNet to generate a segmentation prediction.
They built an image segmentation pipeline to allow biologists and clinical researchers to quantify changes in lung structure during fetal development, and improve understanding of normal lung structure and function.
Using the LungMAP image atlas (http://lungmap.net), the team developed an image segmentation pipeline to help researchers more effectively utilize open-access images of lungs in various developmental stages.
Furthermore, applying an image segmentation and quantification pipeline based on the Fiji imaging platform (Schindelin et al., 2012) to nascent Ubx transcript signals detected in elav and wild-type samples, we observed that elav embryos show both a higher number of transcriptional foci (Fig. 3G, middle) and an overall higher signal intensity level per focus (Fig. 3G, right).
To this end, we developed a custom, fully automated image processing and segmentation pipeline.
simvascular is an open-source software package encompassing an entire cardiovascular modeling and simulation pipeline from image segmentation, three-dimensional (3D) solid modeling, and mesh generation, to patient-specific simulation and analysis.
(a) In experiment 1, the previously un-seen bright-field channel of the test image was fed to the CellProfiler segmentation pipeline containing the trained DCNN.
In this paper, we introduce a simple, yet powerful pipeline for medical image segmentation that combines Fully Convolutional Networks (FCNs) with Fully Convolutional Residual Networks (FC-ResNets).
Additional file 1: General diagram for the CellProfiler pipeline dedicated to image segmentation of GLUT1, HIF1 alpha, KI67 and F4/80 labelled tissue slides.
The systematic pipeline, consisting of four steps including image segmentation, feature calculation, feature extraction and classification, is summarized in Figure 1.
Our automated segmentation pipeline, illustrated in Figure 2, is constituted of 4 successive steps: a coarse segmentation, a stem segmentation, petioles segmentations, and leaves segmentations.
