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Biopsy

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Evaluation of the Classification Accuracy of the Kidney Biopsy Direct Immunofluorescence through Convolutional Neural Networks.

Clinical journal of the American Society of Nephrology : CJASN
BACKGROUND AND OBJECTIVES: Immunohistopathology is an essential technique in the diagnostic workflow of a kidney biopsy. Deep learning is an effective tool in the elaboration of medical imaging. We wanted to evaluate the role of a convolutional neura...

Experimental study of the optimum puncture pattern of robot-assisted needle insertion into hyperelastic materials.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
The robot-assisted insertion surgery plays a crucial role in biopsy and therapy. This study focuses on determining the optimum puncture pattern for robot-assisted insertion, aiming at the matching problem of needle insertion parameters, thereby to re...

Impact of rescanning and normalization on convolutional neural network performance in multi-center, whole-slide classification of prostate cancer.

Scientific reports
Algorithms can improve the objectivity and efficiency of histopathologic slide analysis. In this paper, we investigated the impact of scanning systems (scanners) and cycle-GAN-based normalization on algorithm performance, by comparing different deep ...

Development and evaluation of deep learning-based segmentation of histologic structures in the kidney cortex with multiple histologic stains.

Kidney international
The application of deep learning for automated segmentation (delineation of boundaries) of histologic primitives (structures) from whole slide images can facilitate the establishment of novel protocols for kidney biopsy assessment. Here, we developed...

Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
The Gleason score is the most important prognostic marker for prostate cancer patients, but it suffers from significant observer variability. Artificial intelligence (AI) systems based on deep learning can achieve pathologist-level performance at Gle...

Development and validation of an explainable artificial intelligence-based decision-supporting tool for prostate biopsy.

BJU international
OBJECTIVES: To develop and validate a risk calculator for prostate cancer (PCa) and clinically significant PCa (csPCa) using explainable artificial intelligence (XAI).

Breast cancer detection from biopsy images using nucleus guided transfer learning and belief based fusion.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Breast cancer is a frequently diagnosed cancer in women, contributing to significant mortality rates. Death rates are relatively higher in developing nations due to the shortage of early detection amenities and constraints o...

Impact of radiomics on the breast ultrasound radiologist's clinical practice: From lumpologist to data wrangler.

European journal of radiology
OBJECTIVE: The study aims to assess the impact of radiomics in the clinical practice of breast ultrasound, to determine which lesions are undetermined by the software, and to discuss the future of the radiologist's role.