Search Results - "Ledesma Eriksson, Kajsa"

A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics by Weitz, Philippe, Valkonen, Masi, Solorzano, Leslie, Carr, Circe, Kartasalo, Kimmo, Boissin, Constance, Koivukoski, Sonja, Kuusela, Aino, Rasic, Dusan, Feng, Yanbo, Sinius Pouplier, Sandra, Sharma, Abhinav, Ledesma Eriksson, Kajsa, Latonen, Leena, Laenkholm, Anne-Vibeke, Hartman, Johan, Ruusuvuori, Pekka, Rantalainen, Mattias

“…The analysis of FFPE tissue sections stained with haematoxylin and eosin (H&E) or immunohistochemistry (IHC) is essential for the pathologic assessment of…”
Get full text

Validation of an AI-based solution for breast cancer risk stratification using routine digital histopathology images by Sharma, Abhinav, Lövgren, Sandy Kang, Eriksson, Kajsa Ledesma, Wang, Yinxi, Robertson, Stephanie, Hartman, Johan, Rantalainen, Mattias

“…Stratipath Breast is a CE-IVD marked artificial intelligence-based solution for prognostic risk stratification of breast cancer patients into high- and…”
Get full text

The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue by Weitz, Philippe, Valkonen, Masi, Solorzano, Leslie, Carr, Circe, Kartasalo, Kimmo, Boissin, Constance, Koivukoski, Sonja, Kuusela, Aino, Rasic, Dusan, Feng, Yanbo, Pouplier, Sandra Sinius, Sharma, Abhinav, Eriksson, Kajsa Ledesma, Robertson, Stephanie, Marzahl, Christian, Gatenbee, Chandler D, Anderson, Alexander R. A, Wodzinski, Marek, Jurgas, Artur, Marini, Niccolò, Atzori, Manfredo, Müller, Henning, Budelmann, Daniel, Weiss, Nick, Heldmann, Stefan, Lotz, Johannes, Wolterink, Jelmer M, De Santi, Bruno, Patil, Abhijeet, Sethi, Amit, Kondo, Satoshi, Kasai, Satoshi, Hirasawa, Kousuke, Farrokh, Mahtab, Kumar, Neeraj, Greiner, Russell, Latonen, Leena, Laenkholm, Anne-Vibeke, Hartman, Johan, Ruusuvuori, Pekka, Rantalainen, Mattias

“…The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications. Advances in computing, deep…”
Get full text

The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue by Weitz, Philippe, Valkonen, Masi, Solorzano, Leslie, Carr, Circe, Kartasalo, Kimmo, Boissin, Constance, Koivukoski, Sonja, Kuusela, Aino, Rasic, Dusan, Feng, Yanbo, Pouplier, Sandra Sinius, Sharma, Abhinav, Eriksson, Kajsa Ledesma, Robertson, Stephanie, Marzahl, Christian, Gatenbee, Chandler D., Anderson, Alexander R.A., Wodzinski, Marek, Jurgas, Artur, Marini, Niccolò, Atzori, Manfredo, Müller, Henning, Budelmann, Daniel, Weiss, Nick, Heldmann, Stefan, Lotz, Johannes, Wolterink, Jelmer M., De Santi, Bruno, Patil, Abhijeet, Sethi, Amit, Kondo, Satoshi, Kasai, Satoshi, Hirasawa, Kousuke, Farrokh, Mahtab, Kumar, Neeraj, Greiner, Russell, Latonen, Leena, Laenkholm, Anne-Vibeke, Hartman, Johan, Ruusuvuori, Pekka, Rantalainen, Mattias

“…•largest study to date on multi-stain histopathology image registration.•tissue originates from routine clinical workflows.•the contributions of eight teams…”
Get full text

ACROBAT -- a multi-stain breast cancer histological whole-slide-image data set from routine diagnostics for computational pathology by Weitz, Philippe, Valkonen, Masi, Solorzano, Leslie, Carr, Circe, Kartasalo, Kimmo, Boissin, Constance, Koivukoski, Sonja, Kuusela, Aino, Rasic, Dusan, Feng, Yanbo, Pouplier, Sandra Kristiane Sinius, Sharma, Abhinav, Eriksson, Kajsa Ledesma, Latonen, Leena, Laenkholm, Anne-Vibeke, Hartman, Johan, Ruusuvuori, Pekka, Rantalainen, Mattias

“…The analysis of FFPE tissue sections stained with haematoxylin and eosin (H&E) or immunohistochemistry (IHC) is an essential part of the pathologic assessment…”
Get full text