Comparison workflow automation by registration

Abstract

A method for a rapid automated presentation of at least two radiological data sets of a patient, comprising, (a) automatically registering the data sets in 3D space; and (h) concurrently presenting substantially matching anatomical regions in each data set.

1 .- 30 . (canceled) 
     
     
         31 . A method for a rapid automated presentation of at least two radiological data sets of a patient, comprising:
 (a) loading a current dataset depicting at least one anatomical region of a patient;   (b) automatically retrieving at least one prior dataset depicting the at least one anatomical region from a database;   (c) automatically registering the dataset and the at least one prior dataset in 3D space, using a deforming transformation;   (d) reslicing one or both of the dataset and prior dataset, so that they are sliced along corresponding planes according to the registering; and   (e) concurrently presenting matching anatomical regions in each the data set, comprising at least one slice of one of the datasets and a corresponding slice of the other dataset.   
     
     
         32 . The method of  claim 31 , wherein the automatic registering comprises:
 (a) selecting a point in one of the current dataset and the at least one prior dataset;   (b) automatically identifying a region of interest (ROI) around the point;   (c) identifying an additional ROI in another of the current dataset and the at least one prior dataset; and   (d) performing an automatic volumetric registration of the current dataset and the at least one prior dataset in 3D space according to a volumetric match between the ROI and the additional ROI.   
     
     
         33 . The method of  claim 31 , wherein the current dataset and the at least one prior dataset comprise a member from a group consisting of: a computerized tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), Single photon emission computed tomography (SPECT) or ultrasound (US) scans. 
     
     
         34 . The method of  claim 31 , further comprising:
 (a) assessing the quality of the registration; and   (b) reporting a score indicative of registration quality according to the assessment.   
     
     
         35 . The method of  claim 31 , wherein concurrently presenting comprises:
 (a) manipulating one of the at least two data sets; and   (b) automatically applying the manipulation to a substantially corresponding location in another of the at least two data sets.   
     
     
         36 . The method of  claim 31 , wherein the registering comprises matching between voxels of a first of the current dataset and the at least one prior dataset and respective voxels of a second of the current dataset and the at least one prior dataset while giving greater weight to matching between voxels of one tissue type than to matching between voxels of another tissue type. 
     
     
         37 . The method according to  claim 36 , wherein the matching comprises identifying at least one anatomical structure in the current dataset and the at least one prior dataset and mapping the tissues type and the another tissue type according to the at least one anatomical structure. 
     
     
         38 . The method of  claim 31 , wherein the automatic registering comprises processing at least one of the current dataset and the at least one prior dataset to yield a series of data volumes differing in at least one of a spatial resolution and a color resolution, and performing consecutive intermediate spatial matching steps on the data volumes, using a data volume of increasing resolution at each consecutive step. 
     
     
         39 . The method of  claim 38 , wherein performing the spatial matching steps comprises employing one or both of a different number of degrees of freedom and a different type of degrees of freedom for different steps. 
     
     
         40 . The method of  claim 39 , wherein the different steps comprise a first step of performing matching on a lower resolution data volume and a second step of performing matching on a higher resolution data volume, the first step using at least one translation degree of freedom, and the second step using at least one rotation degree of freedom not used for the first step. 
     
     
         41 . A method for a rapid automated presentation of at least two radiological data sets of a patient, comprising:
 (a) loading a current dataset depicting at least one anatomical region of a patient;   (b) automatically retrieving at least one prior dataset depicting the at least one anatomical region from a database;   (c) automatically registering the dataset and the at least one prior dataset in 3D space; and   (d) concurrently presenting matching anatomical regions in each the data set, performed according to a member of a group consisting of: presenting both the matching anatomical regions as MPRs, presenting a slice on one of the current dataset and the at least one prior dataset and a corresponding MPR on another of the current dataset and the at least one prior dataset the second dataset, presenting a slice of one of the current dataset and the at least one prior dataset and a closest respective slice on another of the current dataset and the at least one prior dataset second dataset, and presenting a corresponding reference point on both one the current dataset and the at least one prior dataset so as to present an arbitrary plane of one of the current dataset and the at least one prior dataset containing the reference point and another arbitrary plane of another of the current dataset and the at least one prior dataset containing the corresponding transformed reference point.   
     
     
         42 . The method of  claim 41 , wherein the automatically registering comprises re-slicing at least one of the current dataset and the at least one prior dataset, and the concurrently presenting is performed based on the re-slicing. 
     
     
         43 . The method of  claim 41 , wherein the automatic registering comprises:
 (a) selecting a point in one of the current dataset and the at least one prior dataset;   (b) automatically identifying a region of interest (ROI) around the point;   (c) identifying an additional ROI in another of the current dataset and the at least one prior dataset; and   (d) performing an automatic volumetric registration of the current dataset and the at least one prior dataset in 3D space according to a volumetric match between the ROI and the additional ROI.   
     
     
         44 . The method of  claim 41 , wherein the current dataset and the at least one prior dataset comprise a member from a group consisting of: a computerized tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), Single photon emission computed tomography (SPECT) or ultrasound (US) scans. 
     
     
         45 . The method of  claim 41 , further comprising:
 (a) assessing the quality of the registration; and   (b) reporting a score indicative of registration quality according to the assessment.   
     
     
         46 . The method of  claim 41 , wherein concurrently presenting comprises:
 (a) manipulating one of the at least two data sets; and   (b) automatically applying the manipulation to a substantially corresponding location in another of the at least two data sets.   
     
     
         47 . The method of  claim 41 , wherein the registering comprises matching between voxels of a first of the current dataset and the at least one prior dataset and respective voxels of a second of the current dataset and the at least one prior dataset while giving greater weight to matching between voxels of one tissue type than to matching between voxels of another tissue type. 
     
     
         48 . The method according to  claim 47 , wherein the matching comprises identifying at least one anatomical structure in the current dataset and the at least one prior dataset and mapping the tissues type and the another tissue type according to the at least one anatomical structure. 
     
     
         49 . The method of  claim 41 , wherein the automatic registering comprises processing at least one of the current dataset and the at least one prior dataset to yield a series of data volumes differing in at least one of a spatial resolution and a color resolution, and performing consecutive intermediate spatial matching steps on the data volumes, using a data volume of increasing resolution at each consecutive step. 
     
     
         50 . The method of  claim 49 , wherein performing the spatial matching steps comprises employing one or both of a different number of degrees of freedom and a different type of degrees of freedom for different steps.