Solution Manual Of Fundamentals Of Digital Image Processing By Anil K Jain 80
Takeshi Krueger
The reader is advised to review the Digital Pathology Association's (DPA) white paper on WSI for an introduction to the technical and workflow aspects of digitizing glass slides.[2] To summarize, the traditional glass histology slide is digitized via a slide scanner and can be viewed on a computer screen or handheld device at a similar resolution as light microscopy. Compared to the general workflow of how tissue sections are prepared and viewed under a microscope, this digital workflow requires additional equipment (e.g., slide scanner, image storage, and digital pathology workstation for viewing), trained personnel, and specific quality control steps (e.g., quality control of scans), all of which require increased information technology and departmental resources.[3] However, there are multiple advantages of transitioning to a digital workflow, including ease of slides and cases sharing (consulting with other pathologists, or collaborating within interdisciplinary research teams), standardization of teaching, organization of archived digitized slides, and extraction of complex data in a highly reproducible fashion via specialized software.[4] The pathologist plays a key role both in the process of slide digitization and in the subsequent data generation via the use of appropriate image analysis algorithms.
Solution Manual Of Fundamentals Of Digital Image Processing By Anil K Jain 80
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Area-based measurements include the most basic assessments, for example, quantifying the areas (2-dimensional) of a certain stain (e.g., chemical or immunohistochemistry [IHC] stain), the area of fat vacuoles, or other events present on a slide. Cell-based measurements aim at identifying and enumerating objects, e.g. cells. This identification of individual cells enables subsequent assessment of subcellular compartments. Finally, algorithms can be utilized to assess events or objects present on tissue sections that may not be comprised of individual cells. More detailed descriptions are given in the following sections. When undertaking assessment and quantification of biomarkers, image analysis tools can be of great value to standardize the analysis as well as minimize bias, subjectivity, and variability in the generated data. This includes the application of standard scoring paradigms to IHC-stained sections (e.g., programmed death-ligand 1 [PD-L1] scoring and human epidermal growth factor receptor 2 [HER2] scoring), as well as aid in the quantification of in situ hybridization (ISH) dots. These assessments can further be tuned to limit the quantification of the present biomarker to tissue compartments (e.g., tumor and stroma) and subcellular compartments (membranous, cytoplasmic, nuclear, or combination thereof), to consider variable staining thresholds, and/or to enable more global biomarker data collection that then can be interrogated in postprocessing steps. In addition, digital tissue image analysis tools can be applied not only to routine formalin-fixed, paraffin-embedded tissues but also to frozen sections, whole organ, and embryo mounts.[6,7,8,9] Similarly, a whole host of staining techniques (and combinations thereof) can be amendable to image analysis, not limited to routine hematoxylin and eosin (H and E) staining, IHC, or ISH labeling (chromogenic and fluorescent).[4,10,11,12,13]
Manual annotations often encompass drawing digital lines (inclusion and exclusion annotations) on whole-slide images to mark an ROI for the algorithm.[4] The algorithm will analyze all tissues included in the inclusion annotation, but omits analysis in that area for tissue regions marked with exclusion annotations. Those exclusions may include tissue structures not deemed for analysis, areas of necrosis, tissue artifacts, and staining artifacts. While manual annotations can be performed by a trained technician, final review and approval by a pathologist is advised.[4]
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