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Track 2: Medical Imaging Digital Pathology

Track 2: Medical Imaging Digital Pathology

Sub track:-
Integration of Imaging Modalities, Advanced Image Analysis, Workflow and Data Management, Enhanced Diagnostic Accuracy. Personalized Medicine, Telemedicine and Remote Diagnostics, Educational Applications, Regulatory and Ethical Considerations, Medical Imaging, DigitalPathology, Pathology Imaging, ImagingInPathology, Digital Health, MedicalImagingTech, PathologyTech, MedicalImagingInnovation, Digital Diagnostics, AIinMedicalImaging

Medical Imaging Digital Pathology refers to the integration of medical imaging techniques, such as MRI, CT scans, and X-rays, with digital pathology, which involves the digitization of traditional pathology practices. This convergence allows for a more comprehensive and accurate approach to diagnosing and understanding diseases. Digital pathology is a process that involves digitizing glass slides to create high-resolution images that can be viewed on a computer or mobile device. The images are then analysed using an image viewer. Digital pathology can be used for many purposes, including: Primary diagnosis, Second opinions, Documentation of lesions, and Precision medicine.
1. Key Components of Medical Imaging in Digital Pathology

a. Whole Slide Imaging (WSI)

Definition: Whole Slide Imaging involves scanning entire glass slides of tissue samples to create high-resolution digital images.

Technology: Utilizes specialized slide scanners that capture detailed, high-resolution images of stained tissue sections.

Benefits: Enables virtual examination of slides, long-term digital storage, and sharing among pathologists.

b. Digital Imaging Systems

Slide Scanners: Devices that convert glass slides into digital formats by capturing high-resolution images of tissue sections.

Imaging Software: Software platforms that allow pathologists to view, annotate, and analyze digital images of tissue samples.

c. Image Analysis

Automated Analysis: Employs algorithms and machine learning models to analyze digital images, assisting in the identification of patterns, tumors, and other anomalies.

Quantitative Analysis: Measures various features within tissue samples, such as cell counts, tumor size, and biomarker expression levels.