ArtIS Development

FocusedON

FocusedON (FN) is a semi-automatic software tool intended for research applications that uses artificial intelligence to extract useful information from computed tomography images stored in DICOM format.

What makes it different

  • FN implements a friendly user interface that allows an intuitive and fast navigation through the DICOM data.
  • FN integrates different submodules, each of them with an specific purpose for a concrete clinical application
  • FN provides precise and objective information useful for the clinical diagnosis and treatment without adding extra work for Radiology.
FN_Logo_512

FocusedON

FocusedON (FN) is a semi-automatic software tool intended for research applications that uses artificial intelligence to extract useful information from computed tomography images stored in DICOM format.

What makes it different

  • FN implements a friendly user interface that allows an intuitive and fast navigation through the DICOM data.
  • FN integrates different submodules, each of them with an specific purpose for a concrete clinical application
  • FN provides precise and objective information useful for the clinical diagnosis and treatment without adding extra work for Radiology.
FN_Logo_512

FocusedON - Body Composition (FN-BC)

FN-BC is a submodule specifically design to carry out a quantitative analysis of the body composition based on abdominal computed tomography image data. It allows to select slices at L3 vertebral level and uses deep learning and artificial intelligence to discriminate accurately muscle and fat, splitting it into visceral, subcutaneous and intramuscular adipose tissue. 

FocusedON - Skeleton (FN-SK)

FN-SK is a submodule that integrates multiple functionalities to study bones structure and density. It permits to select a set of axial CT slices and automatically discriminates the bone tissue using deep learning and artificial intelligence.

FocusedON - Body Composition (FN-BC)

FN-BC is a submodule specifically design to carry out a quantitative analysis of the body composition based on abdominal computed tomography image data. It allows to select slices at L3 vertebral level and uses deep learning and artificial intelligence to discriminate accurately muscle and fat, splitting it into visceral, subcutaneous and intramuscular adipose tissue. 

FocusedON - Skeleton (FN-SK)

FN-SK is a submodule that integrates multiple functionalities to study bones structure and density. It permits to select a set of axial CT slices and automatically discriminates the bone tissue using deep learning and artificial intelligence.