AIMC Topic: Pathology, Clinical

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An Advanced Deep Learning Approach for Ki-67 Stained Hotspot Detection and Proliferation Rate Scoring for Prognostic Evaluation of Breast Cancer.

Scientific reports
Being a non-histone protein, Ki-67 is one of the essential biomarkers for the immunohistochemical assessment of proliferation rate in breast cancer screening and grading. The Ki-67 signature is always sensitive to radiotherapy and chemotherapy. Due t...

Automated histological classification of whole-slide images of gastric biopsy specimens.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: Automated image analysis has been developed currently in the field of surgical pathology. The aim of the present study was to evaluate the classification accuracy of the e-Pathologist image analysis software.

An artificial neural network method for lumen and media-adventitia border detection in IVUS.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Intravascular ultrasound (IVUS) has been well recognized as one powerful imaging technique to evaluate the stenosis inside the coronary arteries. The detection of lumen border and media-adventitia (MA) border in IVUS images is the key procedure to de...

An unsupervised feature learning framework for basal cell carcinoma image analysis.

Artificial intelligence in medicine
OBJECTIVE: The paper addresses the problem of automatic detection of basal cell carcinoma (BCC) in histopathology images. In particular, it proposes a framework to both, learn the image representation in an unsupervised way and visualize discriminati...

[Advances in pathology technology development in China over the past ten years: retrospect and prospect].

Zhonghua bing li xue za zhi = Chinese journal of pathology
Over the past decade, pathology technology in China has undergone rapid development. Through continuous efforts to strengthen normative foundations and quality control, the three-tiered quality control network (national, provincial, and municipal) ha...

Selecting high-throughput scanners for clinical use: A multicenter institution experience.

American journal of clinical pathology
OBJECTIVE: To evaluate and implement whole-slide imaging (WSI) scanners for a fully digital pathology workflow at the University Health Network (UHN) in Canada, a multicenter institution. The goal was to optimize clinical diagnosis, education, telepa...

Digital Pathology and Artificial Intelligence in Pediatric Pathology.

Surgical pathology clinics
Applications of artificial intelligence (AI) and machine learning (ML) are rapidly developing to support the diagnosis and classification of pathology specimens. These tools rely on digitization of pathology glass slides as whole slide images, allowi...

Closing the gap in the clinical adoption of computational pathology: a standardized, open-source framework to integrate deep-learning models into the laboratory information system.

Genome medicine
BACKGROUND: Digital pathology (DP) has revolutionized cancer diagnostics and enabled the development of deep-learning (DL) models aimed at supporting pathologists in their daily work and improving patient care. However, the clinical adoption of such ...