The actual work is devoted to the construction of an individualized mathematical model of the spine, based on the X-ray images in the frontal and sagittal projections using deep learning convolutional neural networks. The semantic segmentation of X-ray images using the convolutional neural network U-Net is performed, also justifying the choice of network parameters and architecture. All stages of the individualized 30 model building are described, the results of each stage are presented. The model is constructed to subsequently determine the type and the extent of scoliosis with the aim of designing and implementing of the Cheneau corset
Automatic localization and identification of vertebrae in medical images of the spine are core requi...
Creation of a Backbone Balancing System Spinal disease detection diagnostics, especially AIS (Adoles...
Precise segmentation and anatomical identification of the vertebrae provides the basis for automatic...
The quality of solving the problem of biomechanical modeling largely depends on the created solid-st...
The aim of the bachelor thesis was to get acquainted with the anatomy and oncological diseases of sp...
This bachelor’s thesis deals with the problem of vertebrae segmentation in CT data with the use of d...
The accurate segmentation and identification of vertebrae presents the foundations for spine analysi...
Scoliosis is a common spinal condition where the spine curves to the side and thus deforms the spine...
Purpose: We present an automated method for extracting anatomical parameters from biplanar radiograp...
Automatic and accurate lumbar vertebrae detection is an essential step of image-guided minimally inv...
International audienceThe goal of this research is reconstructing patient-specific segmented 3-dimen...
Identification of vertebrae type by machine learning is an important task to facilitate the work of ...
Abstract This study proposes a convolutional neural network method for automatic vertebrae detection...
Purpose: This study investigated the segmentation metrics of different segmentation networks trained...
In this doctoral thesis, the design of algorithms enabling the implementation of a fully automatic s...
Automatic localization and identification of vertebrae in medical images of the spine are core requi...
Creation of a Backbone Balancing System Spinal disease detection diagnostics, especially AIS (Adoles...
Precise segmentation and anatomical identification of the vertebrae provides the basis for automatic...
The quality of solving the problem of biomechanical modeling largely depends on the created solid-st...
The aim of the bachelor thesis was to get acquainted with the anatomy and oncological diseases of sp...
This bachelor’s thesis deals with the problem of vertebrae segmentation in CT data with the use of d...
The accurate segmentation and identification of vertebrae presents the foundations for spine analysi...
Scoliosis is a common spinal condition where the spine curves to the side and thus deforms the spine...
Purpose: We present an automated method for extracting anatomical parameters from biplanar radiograp...
Automatic and accurate lumbar vertebrae detection is an essential step of image-guided minimally inv...
International audienceThe goal of this research is reconstructing patient-specific segmented 3-dimen...
Identification of vertebrae type by machine learning is an important task to facilitate the work of ...
Abstract This study proposes a convolutional neural network method for automatic vertebrae detection...
Purpose: This study investigated the segmentation metrics of different segmentation networks trained...
In this doctoral thesis, the design of algorithms enabling the implementation of a fully automatic s...
Automatic localization and identification of vertebrae in medical images of the spine are core requi...
Creation of a Backbone Balancing System Spinal disease detection diagnostics, especially AIS (Adoles...
Precise segmentation and anatomical identification of the vertebrae provides the basis for automatic...