Clinical journal of the American Society of Nephrology : CJASN
Sep 16, 2020
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...
PURPOSE: Current approaches to quantification of magnetic particle imaging (MPI) for cell-based therapy are thwarted by the lack of reliable, standardized methods of segmenting the signal from background in images. This calls for the development of a...
Computer methods and programs in biomedicine
Aug 23, 2020
BACKGROUND AND OBJECTIVE: Chronic kidney disease is a worldwide health issue which includes not only kidney failure but also complications of reduced kidney functionality. Cyst formation, nephrolithiasis or kidney stone, and renal cell carcinoma or k...
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...
Fully convolutional neural network (FCN) has achieved great success in semantic segmentation. However, the performance of the FCN is generally compromised for multi-object segmentation. Multi-organ segmentation is very common while challenging in the...
Nephroblastoma is the most common kidney tumour in children. Its diagnosis is based on imagery. In the SAIAD project, we have designed a platform for optimizing the segmentation of deformed kidney and tumour with a small dataset, using Artificial Int...
Unplanned conversion from minimally invasive surgery (MIS) to open surgery is a significant challenge, although the frequency of conversion for robotic and laparoscopic kidney surgery is not well described. We aimed to compare rates of conversion fo...
Artificial neural networks are the main tools for data mining and were inspired by the human brain and nervous system. Studies have demonstrated their usefulness in medicine. However, no studies have used artificial neural networks for the prediction...
OBJECTIVE: To develop and test the ability of a convolutional neural network (CNN) to accurately identify the presence of renal cell carcinoma (RCC) on histopathology specimens, as well as differentiate RCC histologic subtype and grade.
Radiomics allows for high throughput extraction of quantitative data from images. This is an area of active research as groups try to capture and quantify imaging parameters and convert these into descriptive phenotypes of organs or tumors. Texture a...
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