PATENT CLAIM ANALYSIS

Application Number: 16003707
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-12
Patent Classification: ["345", "634000"]

Abstract:
Systems and methods for standardizing target lesion selection within cross-sectional medical images can include the acts of: (i) sending a plurality of cross-sectional images to a user device, where each cross-sectional image is a cross-sectional slice of digital medical image data captured at a first timepoint from a radiologic device; (ii) receiving a user input identifying a set of pixels corresponding to a target lesion within a cross-sectional image of the plurality of cross-sectional images; and (iii) generating a target lesion location file that includes a precise anatomical location of the cross-sectional image and a pixel location of the target lesion within the cross-sectional image. The systems and methods can additionally include the act of causing a digital marker to be displayed on the cross-sectional image and on each analogous cross-sectional image captured at a later timepoint.

Claim (Index 8):
The computer system as in  claim 6 , wherein, for the target lesion and each of the additional target lesions, the one or more target lesion metrics comprise one or more of:\n a longest dimension length; a short axis dimension length; a craniocaudal dimension length; a longest dimension length of vascularized tumor; a pixel area of the set of pixels; a pixel volume of the set of pixels; a mean value of pixel intensities within the total range of pixel intensities; a mean value of pixel intensities within the subset of pixels; a maximum value of pixel intensities within the total range of pixel intensities; a histogram parameter, wherein the histogram parameter comprises a quantitative distribution of pixel intensities in the set of pixels; and a texture parameter, wherein the texture parameter comprises a first-, second- or third-order statistical characterization of pixel intensities in the set of pixels.

Metadata:
- Claim Count in Document: 28.0
- Percentile: 94.0
- Lexical Diversity: 2.12857
- Patent Class: 345.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15797360', '15407662', '15797391', '11552516', '13305495']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6943276779837394
- 35 USC 102 Novelty (BERT): 0.5169722515340224
- Combined Prediction Score: 0.6765921353387677
- Mean Citation Score: 266.72215800000004
- Max Citation Score: 318.0107
- Similarity Product: 245.23292549533843

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test