Bright field segmentation tomography (BFST) for use as surface identification in stereomicroscopy

Thiesse, Jacqueline; Namati, Eman; Ryk, Jessica de; Hoffman, Eric A.; McLennan, Geoffrey

doi:10.1117/12.529101

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…In fact, if it weren't for the limitations inherent to tissue sectioning a more isotropic data set would have been acquired resulting in a more ideal 3D pathology reconstruction as compared to the volumetric µ-CT reconstruction. Future studies will incorporate airway lengths and branching angle analysis for further morphological information, as well as alveolar size using the optical system developed for the LIMA device [14]. Comparison of different normative strains of mice are also currently being undertaken.…”

Section: Discussionmentioning

confidence: 99%

Three-dimensional visual truth of the normal airway tree for use as a quantitative comparison to micro-CT reconstructions

et al. 2005

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Mouse models are important for pulmonary research to gain insight into structure and function in normal and diseased states, thereby extending knowledge of human disease conditions. The flexibility of human disease induction into mice, due to their similar genome, along with their short gestation cycle makes mouse models highly suitable as investigative tools. Advancements in non-invasive imaging technology, with the development of microcomputed tomography (µ-CT), have aided representation of disease states in these small pulmonary system models. The generation of µ-CT 3D airway reconstructions has to date provided a means to examine structural changes associated with disease. The degree of accuracy of µ-CT is uncertain. Consequently, the reliability of quantitative measurements is questionable. We have developed a method of sectioning and imaging the whole mouse lung using the Large Image Microscope Array (LIMA) as the gold standard for comparison. Fixed normal mouse lungs were embedded in agarose and 250µm sections of tissue were removed while the remaining tissue block was imaged with a stereomicroscope. A complete dataset of the mouse lung was acquired in this fashion. Following planar image registration, the airways were manually segmented using an in-house built software program PASS. Amira was then used render the 3D isosurface from the segmentations. The resulting 3D model of the normal mouse airway tree developed from pathology images was then quantitatively assessed and used as the standard to compare the accuracy of structural measurements obtained from µ-CT.

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Section: Discussionmentioning

confidence: 99%

Three-dimensional visual truth of the normal airway tree for use as a quantitative comparison to micro-CT reconstructions

et al. 2005

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“…The nodules were then imaged using the Siemens MicroCAT II system (Siemens Pre-Clinical, Knoxville, TN) at 80 keV, 100 microA to produce isotropic 28 micron voxels. LIMA subsequently sectioned the tissue at 252 microns and imaged the cut tissue surface at a resolution of 8.5 × 8.5 microns (10 × magnification) (9–12). The LIMA system imaged the tissue surface before cutting and removing the section, hence retaining the spatial correspondence between tissue sections as described in the introduction (Fig 1).…”

Section: Methodsmentioning

confidence: 99%

A Process Model for Direct Correlation between Computed Tomography and Histopathology

et al. 2010

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Rationale and Objectives Multimodal imaging techniques for capturing normal and diseased human anatomy and physiology are being developed to benefit patient clinical care, research, and education. In the past, the incorporation of histopathology into these multimodal datasets has been complicated by the large differences in image quality, content, and spatial association. Materials and Methods We have developed a novel system, the large-scale image microtome array (LIMA), to bridge the gap between nonstructurally destructive and destructive imaging such that reliable registration between radiological data and histopathology can be achieved. Registration algorithms have been designed to align the multimodal datasets, which include computed tomography, computed micro-tomography, LIMA, and histopathology data to a common coordinate system. Results The resulting volumetric dataset provides an abundance of valuable information relating to the tissue sample including density, anatomical structure, color, texture, and cellular information in three dimensions. An image processing pipeline has been established to register all the multimodal data to a common coordinate system. Conclusion In this study, we have chosen to use human lung cancer nodules as an example; however, the flexibility of the image acquisition and subsequent processing algorithms makes it applicable to any soft organ tissue. A novel process model has been established to generate cross registered multimodal datasets for the investigation of human lung cancer nodule content and associated image-based representation.

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“…In addition to the design and development of the LIMA hardware components, a brightfield segmentation tomography (BFST) system has also been created to work in conjunction with the LIMA system (Thiesse et al, 2004). Images acquired en bloc contain a high depth of field.…”

Section: Lighting Techniquesmentioning

confidence: 99%

Large Image Microscope Array for the Compilation of Multimodality Whole Organ Image Databases

Namati

Ryk

Thiesse

et al. 2007

The Anatomical Record

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Three-dimensional, structural and functional digital image databases have many applications in education, research, and clinical medicine. However, to date, apart from cryosectioning, there have been no reliable means to obtain whole-organ, spatially conserving histology. Our aim was to generate a system capable of acquiring high-resolution images, featuring microscopic detail that could still be spatially correlated to the whole organ. To fulfill these objectives required the construction of a system physically capable of creating very fine whole-organ sections and collecting high-magnification and resolution digital images. We therefore designed a large image microscope array (LIMA) to serially section and image entire unembedded organs while maintaining the structural integrity of the tissue. The LIMA consists of several integrated components: a novel large-blade vibrating microtome, a 1.3 megapixel peltier cooled charge-coupled device camera, a high-magnification microscope, and a three axis gantry above the microtome. A custom control program was developed to automate the entire sectioning and automated raster-scan imaging sequence. The system is capable of sectioning unembedded soft tissue down to a thickness of 40 mm at specimen dimensions of 200 3 300 mm to a total depth of 350 mm. The LIMA system has been tested on fixed lung from sheep and mice, resulting in large high-quality image data sets, with minimal distinguishable disturbance in the delicate alveolar structures.

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Bright field segmentation tomography (BFST) for use as surface identification in stereomicroscopy

Cited by 3 publications

References 6 publications

Three-dimensional visual truth of the normal airway tree for use as a quantitative comparison to micro-CT reconstructions

Three-dimensional visual truth of the normal airway tree for use as a quantitative comparison to micro-CT reconstructions

A Process Model for Direct Correlation between Computed Tomography and Histopathology

Large Image Microscope Array for the Compilation of Multimodality Whole Organ Image Databases

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