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Digital image processing for prognostic and diagnostic clinical pathology

Maddison, John (2005) Digital image processing for prognostic and diagnostic clinical pathology. Doctoral thesis, University of Huddersfield.

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When digital imaging and image processing methods are applied to clinical diagnostic
and prognostic needs, the methods can be seen to increase human understanding and
provide objective measurements. Most current clinical applications are limited to
providing subjective information to healthcare professionals rather than providing
objective measures. This Thesis provides detail of methods and systems that have been
developed both for objective and subjective microscopy applications. A system
framework is presented that provides a base for the development of microscopy imaging
systems. This practical framework is based on currently available hardware and
developed with standard software development tools. Image processing methods are
applied to counter optical limitations of the bright field microscope, automating the
system and allowing for unsupervised image capture and analysis.
Current literature provides evidence that 3D visualisation has provided increased
insight and application in many clinical areas. There have been recent advancements in
the use of 3D visualisation for the study of soft tissue structures, but its clinical
application within histology remains limited. Methods and applications have been
researched and further developed which allow for the 3D reconstruction and
visualisation of soft tissue structures using microtomed serial histological sections
specimens. A system has been developed suitable for this need is presented giving
considerations to image capture, data registration and 3D visualisation, requirements.
The developed system has been used to explore and increase 3D insight on clinical
The area of automated objective image quantification of microscope slides
presents the allure of providing objective methods replacing existing objective and
subjective methods, increasing accuracy and rsducinq manual burden. One such
existing objective test is DNA Image Ploidy which seeks to characterise cancer by the
measurement of DNA content within individual cell nuclei, an accepted but manually
burdensome method. The main novelty of the work completed lies in the development of
an automated system for DNA Image Ploidy measurement, combining methods for
automatic specimen focus, segmentation, parametric extraction and the implementation
of an automated cell type classification system.
A consideration for any clinical image processing system is the correct sampling
of the tissue under study. VVhile the image capture requirements for both objective
systems and subjective systems are similar there is also an important link between the
3D structures of the tissue. 3D understanding can aid in decisions regarding the
sampling criteria of objective tests for as although many tests are completed in the 2D
realm the clinical samples are 3D objects. Cancers such as Prostate and Breast cancer
are known to be multi-focal, with areas of seeming physically, independent areas of
disease within a single site. It is not possible to understand the true 3D nature of the
samples using 2D micro-tomed sections in isolation from each other. The 3D systems
described in this report provide a platform of the exploration of the true multi focal nature
of disease soft tissue structures allowing for the sampling criteria of objective tests such
as DNA Image Ploidy to be correctly set.
For the Automated DNA Image Ploidy and the 3D reconstruction and
visualisation systems, clinical review has been completed to test the increased insights
provided. Datasets which have been reconstructed from microtomed serial sections and
visualised with the developed 3D system area presented. For the automated DNA Image
Ploidy system, the developed system is compared with the existing manual method to
qualify the quality of data capture, operational speed and correctness of nuclei
Conclusions are presented for the work that has been completed and discussion
given as to future areas of research that could be undertaken, extending the areas of
study, increasing both clinical insight and practical application.

Item Type: Thesis (Doctoral)
Additional Information: EThOS Persistent ID
Subjects: Q Science > Q Science (General)
R Medicine > RB Pathology
Schools: School of Applied Sciences
Depositing User: Sharon Beastall
Date Deposited: 13 Nov 2014 09:03
Last Modified: 04 Nov 2015 22:34


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