Tensor classification of N-point correlation function features for histology tissue segmentation.

In this paper, we utilize the N-point correlation functions (N-pcfs) to construct an appropriate feature space for achieving tissue segmentation in histology-stained microscopic images. The N-pcfs estimate microstructural constituent packing densities and their spatial distribution in a tissue sample. We represent the multi-phase properties estimated by the N-pcfs in a tensor structure. Using a variant of higher-order singular value decomposition (HOSVD) algorithm, we realize a robust classifier that provides a multi-linear description of the tensor feature space. Validated results of the segmentation are presented in a case-study that focuses on understanding the genetic phenotyping differences in mouse placentae.

An imaging workflow for characterizing phenotypical change in large histological mouse model datasets.

MOTIVATION: This paper presents a workflow designed to quantitatively characterize the 3D structural attributes of macroscopic tissue specimens acquired at a micron level resolution using light microscopy. The specific application is a study of the morphological change in a mouse placenta induced by knocking out the retinoblastoma gene. RESULT: This workflow includes four major components: (i) serial section image acquisition, (ii) image preprocessing, (iii) image analysis involving 2D pair-wise registration, 2D segmentation and 3D reconstruction, and (iv) visualization and quantification of phenotyping parameters. Several new algorithms have been developed within each workflow component. The results confirm the hypotheses that (i) the volume of labyrinth tissue decreases in mutant mice with the retinoblastoma (Rb) gene knockout and (ii) there is more interdigitation at the surface between the labyrinth and spongiotrophoblast tissues in mutant placenta. Additional confidence stem from agreement in the 3D visualization and the quantitative results generated. AVAILABILITY: The source code is available upon request.

Detection and visualization of surface-pockets to enable phenotyping studies.

In this paper, we propose a technique for detecting pockets on a surface-of-interest. A sequence of propagating fronts converging to the target surface is used as the basis for inspection. We compute a correspondence function between the initial and the target surface. This leads to a natural definition of the local feature size measured as the evolution distance between mapped points. Surface pockets are then extracted as salient clusters embedded in the feature space. The level-set initialization also determines the scale-space of the extracted pockets. Results are presented on a case-study in which the focus is to chronicle the phenotyping differences in genetically modified mouse placenta. Our results are validated based on manually verified ground-truth.

Rb is critical in a mammalian tissue stem cell population.

The inactivation of the retinoblastoma (Rb) tumor suppressor gene in mice results in ectopic proliferation, apoptosis, and impaired differentiation in extraembryonic, neural, and erythroid lineages, culminating in fetal death by embryonic day 15.5 (E15.5). Here we show that the specific loss of Rb in trophoblast stem (TS) cells, but not in trophoblast derivatives, leads to an overexpansion of trophoblasts, a disruption of placental architecture, and fetal death by E15.5. Despite profound placental abnormalities, fetal tissues appeared remarkably normal, suggesting that the full manifestation of fetal phenotypes requires the loss of Rb in both extraembryonic and fetal tissues. Loss of Rb resulted in an increase of E2f3 expression, and the combined ablation of Rb and E2f3 significantly suppressed Rb mutant phenotypes. This rescue appears to be cell autonomous since the inactivation of Rb and E2f3 in TS cells restored placental development and extended the life of embryos to E17.5. Taken together, these results demonstrate that loss of Rb in TS cells is the defining event causing lethality of Rb(-/-) embryos and reveal the convergence of extraembryonic and fetal functions of Rb in neural and erythroid development. We conclude that the Rb pathway plays a critical role in the maintenance of a mammalian stem cell population.