FUJIFILM

AI technology to segment and quantify the volume of each brain regions.
This technology can be used for pre-surgery simulation or calculation of the atrophy rate for each region between past and current exams.

This technology visualizes the bone density temporal difference by performing image registration between the past and current image of the same patient.
The increase and decrease in CT value will be highlighted.

This technology which developed by deep learning will automatically detect the lumbar spine and femur bone that enhanced by energy subtraction, and calculate the bone mineral density.

Automatically extracts the pancreas, each surrounding organ area, and surrounding vessels from contrast-enhanced CT images and analyzes them in 3D.
The pancreatic duct diameter, residual pancreatic volume, measurement of the cross-sectional area, and resection simulation can be performed to support pancreatic surgery.

AI technology to extract each kidney and surrounding vessels from CT or MRI images assists volume calculation of renal and compare current and past results.
This technology can also precisely extract cystic kidneys, a genetic disease that is often difficult to extract due to the diversity of shapes, and assist diagnosis and treatment.

AI technology to automatically extract liver vessels and then labels liver according to the anatomic liver segments (Couinaud segments) based on the vessel running.
This can be used for Interventional Radiology planning for liver.

Technology that automatically extracts the liver parenchyma and surrounding vessels from CT images and analyzes them in 3D.
This technology can assist preoperative simulation by planning resection area based on the calculation of the dominant vessels.

AI technology to automatically extract lung fields, 5 lobes, and bronchus,　surrounding vessels from CT images.
From each extraction result, the percentage of low attenuation area is calculated.
These are expected to contribute the diagnosis of COPD.

This technology automatically extracts the femur, tibia, patella, cartilage, and meniscus from MRI images.
By measuring the thickness of the cartilage and the distance between the meniscus and tibia, it is possible to evaluate the condition of the knee joint without invasion.

Technology to recognize each vertebral body individually and label the vertebrae and ribs. This reduces the burden on the physician of visually counting bone positions. It is also used for visualization of fractures and bone metastasis by subtraction of rigid body alignment of vertebral bodies.

AI technology to subdivide lung into 10 segments in right lung, 8 segments in left lung from CT images. It can be used for confirming the position of chest nodules detected by a doctor.

AI technology to segment relatively large mediastinum, axillary lymph node from CT images. This technology can be used for assessment of lymph node enlargement.