Digital Pathology: Roadmap to the Future of Medical Diagnosis

Digital Pathology: Roadmap to the Future of Medical Diagnosis

Digital Pathology solutions and Artificial Intelligence tools are destined to transform efficiency and workflow of Pathology services

RELEASE DATE
29-Dec-2018
REGION
Global
Research Code: D888-01-00-00-00
SKU: HC03121-GL-TR_22728
$4,950.00
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HC03121-GL-TR_22728
$4,950.00
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Description

Digital Pathology encompasses the use of optmized pathology workstations, whole slide imaging, image analysis, image management, laboratory information management system, use of machine learning, data handling and storage. Pathology is one of the most important fields in medicine, as the service provides investigation and validation platform in lieu of a medical condition of a patient. Traditional methods of pathology involves slide preparation, traditional microscopy, result interpretation from microscopy by pathologist onto an information management system followed by physical storage of slides for a prescribed timeline. According to numerous research and surveys conducted across the world, the request for pathology services are increasing by a healthy percentage year-on-year which can be attributed to the increase in cancer prevalence across the globe, ageing population amongst a number of other factors. Factoring in to the above the number of experienced pathologists available at the moment and ones about to retire, the scenario for pathology services may start to look grim. Therefore, an urgent solution is needed to tackle the challenges pertaining increase in diagnosis of patients and unreasonable timelines that pathologists are facing currently with the traditional pathology methods. Proper deployment of Digital Pathology solutions have the demonstrated ability to streamline the workflow of pathology services, and can potentially increase the efficiency of the workflow and decrease the time for diagnosis.

Artificial Intelligence (AI), Machine learning and deep learning are terms that refer to the technology that possesses the ability to recognize patterns from the database that it is initially provided with and matching to it to similar data set thus mapping the results based on past occurrences. The use of AI in digital pathology has gained momentum over the last few years. Notably, the FDA approved an AI-tool as a primary diagnosis tool as recently as in 2017 for wrist fractures. The application of AI for pathology services are innumerable considering the fact the pathological services give rise to a lot of information. Information or data sets that can serve as the basis of creating deep learning digital pathology tools that can act as a diagnosis supplement tool for pathologists, thus increasing the speed of diagnosis, maybe accuracy and certainly providing the potential to prioritize diagnosis cases based on severity for the pathologists to review. The next decade of the medical field is set to witness the transformation of digital pathology services by AI tools.

Table of Contents

1.1 Research Objectives

1.2 Research Methodology

1.3 Overview of Business and Market Segmentation of Digital Pathology Industry

1.4 Key Findings: Digital Pathology and Artificial Intelligence (AI)

2.1 Digital Pathology: Current Workflow and Future Possibilities

2.2 Technology Segmentations of Digital Pathology

2.3 Fields of Application

2.4 Business Models

2.5 Strategic Design Needs to Improve Commercialization

3.1 Impact of Cloud Technology on Digital Pathology

4.1 Whole Slide Imaging (WSI) is Paramount to Digital Pathology

4.2 Efficient WSI Integration for Improved workflow

5.1 Image Analysis Software

6.1 Artificial Intelligence- Introduction

6.2 Focus Areas of AI companies in Digital Pathology

6.3 Important Advances in AI Capabilities in Digital pathology

7.1 Smooth Transitioning Innate to Successful Adoption of Technology

7.2 Digital Pathology Adoption needs a Phased Approach

7.3 Strategic Technology Integration and Personnel Training pays Dividends

7.4 Phased workflow implementation provides numerous benefits

8.1 Factors Affecting Adoption of AI in Digital Pathology

9.1 Aiforia and ContextVision- Company Profile

9.2 Deciphex and Indica Labs- Company Profile

9.3 Barco & Inspirata- Company Profile

9.4 Leica Biosystems & Flagship Biosciences- Company Profile

10.1 Patent Research Scope and Concepts

10.2 Top 10 Patent Holding Companies in Digital Pathology Technologies

10.3 Top 10 Patent Holding Educational Institutes in Digital Pathology Technologies

10.4 Office-wise Distribution of Digital Pathology Patent Portfolio, 2008-2018*

10.5 Year-wise Distribution of Digital Pathology Portfolio, 2008–2018*

11.1 Growth Opportunity 1: Optimal use of Big Data Key for AI Advancement in Digital Pathology

11.2 Growth Opportunity 2: Generation of Datasets for Validation Paramount to Overcome Regulatory Hurdles

11.3 Growth Opportunity 3: Transitioning from Pharmaceutical Industry Application to Mainstream Clinical Applications

12.1 Key Contacts

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Related Research
Digital Pathology encompasses the use of optmized pathology workstations, whole slide imaging, image analysis, image management, laboratory information management system, use of machine learning, data handling and storage. Pathology is one of the most important fields in medicine, as the service provides investigation and validation platform in lieu of a medical condition of a patient. Traditional methods of pathology involves slide preparation, traditional microscopy, result interpretation from microscopy by pathologist onto an information management system followed by physical storage of slides for a prescribed timeline. According to numerous research and surveys conducted across the world, the request for pathology services are increasing by a healthy percentage year-on-year which can be attributed to the increase in cancer prevalence across the globe, ageing population amongst a number of other factors. Factoring in to the above the number of experienced pathologists available at the moment and ones about to retire, the scenario for pathology services may start to look grim. Therefore, an urgent solution is needed to tackle the challenges pertaining increase in diagnosis of patients and unreasonable timelines that pathologists are facing currently with the traditional pathology methods. Proper deployment of Digital Pathology solutions have the demonstrated ability to streamline the workflow of pathology services, and can potentially increase the efficiency of the workflow and decrease the time for diagnosis. Artificial Intelligence (AI), Machine learning and deep learning are terms that refer to the technology that possesses the ability to recognize patterns from the database that it is initially provided with and matching to it to similar data set thus mapping the results based on past occurrences. The use of AI in digital pathology has gained momentum over the last few years. Notably, the FDA approved an AI-tool as a primary diagnosis tool as recently as in 2
More Information
No Index No
Podcast No
Author Deepak Jayakumar
Industries Healthcare
WIP Number D888-01-00-00-00
Is Prebook No