A computer-implemented method of detecting and quantifying a spinal curve is disclosed herein. The method comprises obtaining a Forward-Looking Infrared Radiometer (FLIR) camera, calibrating the FLIR camera to room temperature, stabilizing the FLIR camera for imaging of a spine of a subject at a position horizontally spaced about ½ to about 3 meters, or about ½ to about 2 meters, from the camera, scanning at least a portion of the spine with the FLIR camera to obtain thermal data, and generating an image of the subject's spine. Corresponding systems and methods also are disclosed.

A system and method for providing a guided workflow through a series of ultrasound image acquisitions with reference images updated based on a determined anatomical position is provided. The method includes acquiring and displaying, by an ultrasound system, at least one ultrasound image of an anatomy. The method includes determining, by at least one processor, a position of the anatomy depicted in the at least one ultrasound image. The method includes automatically selecting and displaying, by the at least one processor, reference images corresponding to pre-defined views of an ultrasound examination. An orientation of anatomy depicted in the selected and displayed reference images is based on the determined position of the anatomy. The method includes acquiring and displaying, by the ultrasound system, additional ultrasound images of the anatomy corresponding to the selected and displayed reference images. The additional ultrasound images include pre-defined views of the ultrasound examination.

Systems, instruments, and methods for medical treatment. The methods comprise, by a computing device: receiving information identifying at least one first point on a body part shown in a medical image; overlaying a first mark on the medical image for the at least one first point; generating a spline based at least on the first mark; overlaying a second mark for the spline on the medical image; identifying a location of at least one second point on the body part shown in the medical image based on the first and second marks; overlaying a third mark for the at least one second point on the medical image; and using at least the third mark to facilitate the medical treatment of an individual whose body part is shown in the medical image.

A system for executing a three-dimensional (3D) intraoperative scan of a patient is disclosed. A 3D scanner controller projects the object points included onto a first image plane and the object points onto a second image plane. The 3D scanner controller determines first epipolar lines associated with the first image plane and second epipolar lines associated with the second image plane based on an epipolar plane that triangulates the object points included in the first 2D intraoperative image to the object points included in the second 2D intraoperative image. Each epipolar lines provides a depth of each object as projected onto the first image plane and the second image plane. The 3D scanner controller converts the first 2D intraoperative image and the second 2D intraoperative image to the 3D intraoperative scan of the patient based on the depth of each object point provided by each corresponding epipolar line.

A framework for patient management based on anatomic measurements is described herein. In accordance with one aspect, patient records are clustered into a set of sub-populations based on first anatomic measurements and characteristics extracted from first patient data associated with a population of patients. A representative sub-population similar to a patient may be determined from the set of sub-populations based on the patient data of the patient. A report that presents the second anatomic measurements associated with the patient in relation to corresponding first anatomic measurements associated with the representative sub-population may then be generated.

Described herein is a novel method and system for segmentation of the spine using 3D volumetric data. In embodiments, a method includes an extracting step, localization step, and segmentation step. The extracting step comprises detecting the spine centerline and the spine canal centerline. The localization step comprises localizing the vertebra and intervertebral disc centers. Background and foreground constraints are created for each vertebra digit. Segmentation is performed for each vertebra digit and based on the hard constraints.

The present disclosure relates to a method and apparatus for automatic thoracic organ segmentation. The method includes: receiving three-dimensional (3D) images obtained by a computed tomography (CT) system; processing the 3D images to have the same spatial resolution and matrix size; building a two-stage deep learning framework using convolutional neural networks (CNNs) for organ segmentation; adapting the deep learning framework to be compatible with incomplete training data; improving the CNNs upon arrival of new training data; post-processing the output from the deep learning framework to obtain final organ segmentation.

According to the invention, the process includes the steps of: a) taking a sagittal preoperative x-ray of the vertebral column of the patient to be treated, extending from the cervical vertebrae to the femoral heads; b) on that x-ray, identifying points on S1, S2, T12 et C7; c) depicting, on the said x-ray, curved segments beginning at the center of the plate of S1 et going to the center of the plate of C7; e) identifying, on that x-ray, the correction(s) to be made to the vertebral column, including the identification of posterior osteotomies to make; f) pivoting portions of said x-ray relative to other portions of that x-ray, according to osteotomies to be made; g) performing, on said x-ray, a displacement of the sagittal curvature segment extending over the vertebral segment to be corrected; h) from a straight vertebral rod (TV), producing the curvature of that rod according to the shape of said sagittal curvature segment in said displacement position.

Systems and methods for visualization of a surgical site are disclosed. An imaging device provides image data of the surgical site. A computing device detects, in the image data, at least one obstruction. The computing device filters the image data to remove the at least one obstruction by being configured to alter pixels related to the at least one obstruction based on at least one of (i) one or more buffered frames and (ii) one or more pixels adjacent to the pixels related to the at least one obstruction. The computing device generates an output from the filtered image data. A display device presents the output for visualization of the surgical site.

A system for surgical planning and assessment of spinal deformity correction is provided that has a spinal imaging system and a control unit. The spinal imaging system is configured to collect at least one digitized position of one or more vertebral bodies of a subject. The control unit is configured to receive the at least one digitized position, and calculate, based on the at least one digitized position, an optimized posture for the subject. The control unit is configured to receive one or more simulated spinal correction inputs, and based on the inputs and optimized posture, predict an optimal simulated postoperative surgical correction.