Search Results - "Perslev, M."

Validation of an open source, generic deep learning architecture for 3D MRI segmentation - with data from the OAI, PROOF, and CCBR by Perslev, M., Pai, A., Igel, C., Runhaar, J., Dam, E.B.

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MULTI-INSTITUTIONAL LARGE-SCALE VALIDATION OF 8 METHODS FOR AUTOMATIC KNEE MRI SEGMENTATION FOR USE IN CLINICAL TRIALS by Dam, E.B., Desai, A., Deniz, C., Rajamohan, H., Regatte, R., Iriondo, C., Pedoia, V., Majumdar, S., Perslev, M., Igel, C., Pai, A., Gaj, S., Yang, M., Nakamura, K., Li, X., Maqbool, H., Irmakci, I., Song, S-E., Bagci, U., Hargreaves, B., Gold, G., Chaudhari, A.

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A multi-institute automated segmentation evaluation on a standard dataset: Findings from the international workshop on osteoarthritis imaging segmentation challenge by Desai, A., Caliva, F., Iriondo, C., Khosravan, N., Mortazi, A., Jambawalikar, S., Torigian, D., Ellermann, J., Akcakaya, M., Bagci, U., Tibrewala, R., Flament, I., O'Brian, M., Majumdar, S., Perslev, M., Pai, A., Igel, C., Dam, E., Gaj, S., Yang, M., Nakamura, K., Li, X., Deniz, C., Juras, V., Regatte, R., Gold, G., Hargreaves, B., Pedoia, V., Chaudhari, A.

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