SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps

Research output: Chapter in Book/Report/Conference proceedings › Chapter › peer-review

Original language	Undefined/Unknown
Title of host publication	SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps
DOIs	https://doi.org/10.1007/978-3-031-63803-9_1
Publication status	Published - 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

@inbook{f4012bb4d88c4950b82f729ec88025a0,

title = "SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps",

author = "Oleksandr Davydko and Vladimir Pavlov and Przemys{\l}aw Biecek and Luca Longo",

year = "2024",

doi = "10.1007/978-3-031-63803-9\_1",

language = "Undefined/Unknown",

booktitle = "SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps",

}

SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps. / Davydko, Oleksandr; Pavlov, Vladimir; Biecek, Przemysław et al.
SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps. 2024.

Research output: Chapter in Book/Report/Conference proceedings › Chapter › peer-review

TY - CHAP

T1 - SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps

AU - Davydko, Oleksandr

AU - Pavlov, Vladimir

AU - Biecek, Przemysław

AU - Longo, Luca

PY - 2024

Y1 - 2024

UR - https://doi.org/10.1007/978-3-031-63803-9_1

U2 - 10.1007/978-3-031-63803-9_1

DO - 10.1007/978-3-031-63803-9_1

M3 - Chapter

BT - SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps

ER -