Dave's PCF WIP: Paragraphs

Paragraphs

Actions	Matter	Content	Para #	Notes	Modified
View Edit Delete	PER-8 PROV	As used herein, "segmentation" or "image segmentation" refers the process of partitioning an image into different meaningful segments. These segments may correspond to different tissue classes, organs, pathologies, bones, or other biologically relevant structures. Medical image segmentation accommodates imaging ambiguities such as by low contrast, noise, and other imaging ambiguities.	141	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	Certain computer vision techniques can be used or adapted for image segmentation. For example, the techniques and or algorithms for segmentation may include, but are not limited to: Atlas-Based Segmentation: For many applications, a clinical expert can manually label several images; segmenting unseen images is a matter of extrapolating from these manually labeled training images. Methods of this style are typically referred to as atlas-based segmentation methods. Parametric atlas methods typically combine these training images into a single atlas image, while nonparametric atlas methods typically use all of the training images separately. Atlas-based methods usually require the use of image registration in order to align the atlas image or images to a new, unseen image.	142	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	In certain embodiments, the patient-specific cutting guide can be used to preposition and pre-drill a plate system for fixation purposes. Such plate systems may be optimally placed, per a CT scan, after a correction procedure for optimal fixation outcome. In another embodiment, the CAD model and/or automated process such as advanced computer analysis, machine learning and automated/artificial intelligence may be used to measure a depth of the cut through the patient-specific cutting guide for use with robotics apparatus and/or systems which would control the depth of each cut within the guide to protect vital structures below or adjacent to a bone being cut. In another embodiment, the CAD model and/or automated process such as advanced computer analysis, machine learning and automated/artificial intelligence may be used to define desired fastener (e.g. bone screw) length and/or trajectories through a patient-specific cutting guide and/or implant. The details for such lengths, trajectories, and components can be detailed in a report provided to the surgeon preparing to do a procedure.	47	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	In one embodiment, the method 1700 begins after a bone model of a patient’s body or body part(s) is generated. In a first step 1702, the method 1700 may review the bone model and data associated with the bone model to determine anatomic data of a patient’s foot.	144	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	After step 1702, the method 1700 determine 1704 a deformity in the patient’s anatomy using the anatomic data. In certain embodiments, the detection and/or identification of a deformity may employ advanced computer analysis, expert systems, machine learning, and/or automated/artificial intelligence. As used herein, "artificial intelligence" refers to intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals, which involves consciousness and emotionality. The distinction between artificial intelligence and natural intelligence categories is often revealed by the acronym chosen. 'Strong' AI is usually labelled as artificial general intelligence (AGI) while attempts to emulate 'natural' intelligence have been called artificial biological intelligence (ABI). Leading AI textbooks define the field as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of achieving its goals. The term "artificial intelligence" can also be used to describe machines that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem solving". (Search "artificial intelligence" on Wikipedia.com June 25, 2021. CC-BY-SA 3.0 Modified. Accessed June 25, 2021.) Various kinds of deformities may be identified, such as a bunion. The deformities determined may include congenital as well as those caused by injury or trauma.	145	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	Next, the method 1700 proceeds and a template cutting guide model is selected 1706 from a repository of template cutting guide models. A template cutting guide model is a model of a template cutting guide.	146	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	As used herein, "template cutting guide" refers to a guide configured, designed, and/or engineered to serve as a template for creating, generating, or fabricating a patient specific cutting guide. In one aspect, the template cutting guide may be used, as-is, without any further changes, modifications, or adjustments and thus become a patient specific cutting guide. In another aspect, the template cutting guide may be modified, adjusted, or configured to more specifically address the goals, objectives, or needs of a patient or a surgeon and by way of the modifications become a patient specific cutting guide. The patient specific cutting guide can be used by a user, such as a surgeon, to guide making one or more resections of a structure, such as a bone for a procedure. Accordingly, a template cutting guide model can be used to generate a patient specific cutting guide model. The patient specific cutting guide model may be used in a surgical procedure to address, correct, or mitigate effects of the identified deformity and may be used to generate a patient specific cutting guide that can be used in a surgical procedure for the patient.	147	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	"Repository" refers to any data source or dataset that includes data or content. In one embodiment, a repository resides on a computing device. In another embodiment, a repository resides on a remote computing or remote storage device. A repository may comprise a file, a folder, a directory, a set of files, a set of folders, a set of directories, a database, an application, a software application, content of a text, content of an email, content of a calendar entry, and the like. A repository, in one embodiment, comprises unstructured data. A repository, in one embodiment, comprises structured data such as a table, an array, a queue, a look up table, a hash table, a heap, a stack, or the like. A repository may store data in any format including binary, text, encrypted, unencrypted, a proprietary format, or the like.	148	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	Next, the method 1700 may register 1708 the template cutting guide model with one or more bones of the bone model. This step 1708 facilitates customization and modification of the template cutting guide model to generate a patient specific cutting guide model from which a patient specific cutting guide can be generated. The registration step 1708 combines two models and/or patient imaging data and positioned both models for use in one system and/or in one model.	149	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	As used herein, "registration" or " image registration" refers to a method, process, module, component, apparatus, and/or system that seeks to achieve precision in the alignment of two images. As used here, "image" may refer to either or both an image of a structure or object and another image or a model (e.g., a computer based model or a physical model, in either two dimensions or three dimensions). In the simplest case of image registration, two images are aligned. One image may serve as the target image and the other as a source image; the source image is transformed, positioned, realigned, and/or modified to match the target image. An optimization procedure may be applied that updates the transformation of the source image based on a similarity value that evaluates the current quality of the alignment. An iterative procedure of optimization may be repeated until a (local) optimum is found. An example is the registration of CT and PET images to combine structural and metabolic information. Image registration can be used in a variety of medical applications: Studying temporal changes; Longitudinal studies may acquire images over several months or years to study long-term processes, such as disease progression. Time series correspond to images acquired within the same session (seconds or minutes). Time series images can be used to study cognitive processes, heart deformations and respiration; Combining complementary information from different imaging modalities. One example may be the fusion of anatomical and functional information.	150	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	Since the size and shape of structures vary across modalities, evaluating the alignment quality can be more challenging. Thus, similarity measures such as mutual information may be used; Characterizing a population of subjects. In contrast to intra-subject registration, a one-to-one mapping may not exist between subjects, depending on the structural variability of the organ of interest. Inter-subject registration may be used for atlas construction in computational anatomy. Here, the objective may be to statistically model the anatomy of organs across subjects; Computer-assisted surgery: in computer-assisted surgery pre-operative images such as CT or MRI may be registered to intra-operative images or tracking systems to facilitate image guidance or navigation. There may be several considerations made when performing image registration: The transformation model. Common choices are rigid, affine, and deformable transformation models. B-spline and thin plate spline models are commonly used for parameterized transformation fields. Non-parametric or dense deformation fields carry a displacement vector at every grid location; this may use additional regularization constraints. A specific class of deformation fields are diffeomorphisms, which are invertible transformations with a smooth inverse; The similarity metric. A distance or similarity function is used to quantify the registration quality. This similarity can be calculated either on the original images or on features extracted from the images. Common similarity measures are sum of squared distances (SSD), correlation coefficient, and mutual information. The choice of similarity measure depends on whether the images are from the same modality; the acquisition noise can also play a role in this decision. For example, SSD may be the optimal similarity measure for images of the same modality with Gaussian noise. However, the image statistics in ultrasound may be significantly different from Gaussian noise, leading to the introduction of ultrasound specific similarity measures.	151	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	Multi-modal registration may use a more sophisticated similarity measure; alternatively, a different image representation can be used, such as structural representations or registering adjacent anatomy; The optimization procedure. Either continuous or discrete optimization is performed. For continuous optimization, gradient-based optimization techniques are applied to improve the convergence speed.(Search "medical image computing" on Wikipedia.com June 24, 2021. CC-BY-SA 3.0 Modified. Accessed June 25, 2021.)	152	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	Next, the method 1700 may design 1710 a patient specific cutting guide model based on the template cutting guide model. The design step 1710 may be completely automated or may optionally permit a user to make changes to a template cutting guide model or partially completed patient specific cutting guide model before the patient specific cutting guide model is complete. A template cutting guide model and patient specific cutting guide model are two examples of an instrument model. As used herein, "instrument model" refers to a model, either physical or digital, that represents an instrument, tool, apparatus, or device. Examples, of an instrument model can include a cutting guide model, a patient specific cutting guide model, and the like. In one embodiment, a patient specific cutting guide and a patient specific cutting guide model may be unique to a particular patient and that patient’s anatomy and/or condition.	153	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	The method 1700 may conclude by a step 1712 in which patient specific cutting guide may be manufactured based on the patient specific cutting guide model. Various manufacturing tools, devices, systems, and/or techniques can be used to manufacture the patient specific cutting guide. As used herein, “manufacturing tool” or "fabrication tool" refers to a manufacturing or fabrication process, tool, system, or apparatus which creates an object, device, apparatus, feature, or component using one or more source materials. A manufacturing tool or fabrication tool can use a variety of manufacturing processes, including but not limited to additive manufacturing, subtractive manufacturing, forging, casting, and the like. The manufacturing tool can use a variety of materials including polymers, thermoplastics, metals, biocompatible materials, biodegradable materials, ceramics, biochemicals, and the like. A manufacturing tool may be operated manually by an operator, automatically using a computer numerical controller (CNC), or a combination of these techniques.	154	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	Figure 18 illustrates an exemplary system 1800 configured to generate one or more patient specific instruments configured to correct a bone condition, according to one embodiment. The system 1800 may include an apparatus 1802 configured to accept, review, receive or reference a bone model 1804 and provide a patient specific cutting guide 1806. In one embodiment, the apparatus 1802 is a computing device. In another embodiment, the apparatus 1802 may be a combination of computing devices and/or software components or a single software component such as a software application.	155	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	Figure 6A is a perspective view of the foot of Figure 2, after resection of the first cuneiform and the first metatarsus, removal of the cutting guide, and placement of the first metatarsus to abut the first cuneiform, according to one embodiment.	30	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	FIG. 14 illustrates a 3D color perspective view of a first cuneiform and first metatarsus with one embodiment of a cutting guide secured to the two bones.	39	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	FIG. 13 illustrates a 3D color perspective view of a first cuneiform and first metatarsus with one embodiment of a cutting guide secured to the two bones.	38	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	Figures 12A, 12B, 12C, 12D, 12E, 12F, 12G, and 12H are top perspective, top, bottom, front elevation, rear elevation, right, left, and alternative top perspective, respectively, of a patient-specific cutting guide according to one alternative embodiment.	37	Added by DJM 7 2021	7/2/21, 12:00 AM
View Edit Delete	PER-8 PROV	Figure 11 is a perspective view of the implant of Figure 10, in isolation, according to one embodiment.	36	Added by DJM 7 2021	7/2/21, 12:00 AM

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