Dave's Patent Content Factory
Applications
Terms
Paragraphs
Claims
Docket
Logout
About
Paragraph #7,753
Edit Paragraph
View
List Paragraphs
Delete
Application
2380.2.01
US-20150012794-A1
US-20150205664-A1
US-20100023800-A1
US-8737141-A1
US-10157004-B2
US10007433A1
US-9159419-B2
US-10114589-A1
US-10134728-A1
US-20200065270-A1
US-10637533-B2
US-9927986-A1
US-8380915-A1
US-9159419-A1
US-9208071-A1
US-20200098728-A1
US-10643676-A1
US-10468073-B2
US-10283200-A1
US-10461965-B1
US-20130279232-A1
US-8892980-B2
US9632727A1
US10558561A1
US20100023800A1
US7230213A1
OPT-9
FLO-2
FLO-5PROV
ONSO3175(B) - Onsemi378
ONSO3305US - Onsemi346
GTS-3DES
FLO-4
US8762658B2
US8533406B2
US9632727B2
KMN-1PROV
PAT-2
PER-8 PROV
PER-9 PROV
INS-4PROV
HAR-1
CES-16
NXT-5PROV NXT-5, 6, 7, 8
IPP-0051-US14 cross roads
FLO-7PROV
IMI-5PROV
IPP-0050-US35 nextremity
VIL-12
OPT-13
TOY-1
US10998041B1
FSP1845
US6559866B2
Placeholder App
PER-10
KBR-1 1400.2.623
PER-13PROV
PAT-3
US20030023453
RMS-1DES
SMG-1DES
FLO-5
US10318495
US10133662B2
PER-11
US20140066758
VIL-17
PER-17
JBR-1
PER-12
US11056880
US11302645
US20210407565
US11081191
PON-1PROV, 2PROV, 3PROV
PER-33
RMT-1PROV
PER-32
PER-34
MCC-1
FLO-10
PER-14
PER-19
PER-22
PER-18
PER-24
TMC-PAT-1
DAR-2
PER-23
TMC-PAT-4
PER-16
PER-4 DIV1
PER-20
PER-21
BRT-PAT-1
TMC-PAT-5
TMC-PAT-6PROV
BRT-PAT-2-PROV
71212.157.USU1
FPR-PAT-1-PROV
71212.158.USP1
RMT-1
DAR-1PROV
DAR-2PROV
PON-1PROV
PON-2PROV
PON-3PROV
PER-18PROV
TMC-1PROV
TMC-2PROV
PER-13PCT
PER-13
PER-16PROV
PER-14PROV
PER-34PROV
TMC-4PROV
TMC-3
PAS-1PROV
VEH-1
PER-29DES
TEST.001
E2E-TEST.001
TEST-001
TEST-002
TEST-003
TEST-004
ZED006
FSP1011
GAV-PAT-1-PROV
Matter Number
Paragraph Number
58
Application Number
Reference Case 1
Reference Case 2
Content
As used herein, "medical image computing" or "medical image processing" refers to systems, software, hardware, components, and/or apparatus that involve and combine the fields of computer science, information engineering, electrical engineering, physics, mathematics and medicine. Medical image computing develops computational and mathematical methods for working with medical images and their use for biomedical research and clinical care. One goal for medical image computing is to extract clinically relevant information or knowledge from medical images. While closely related to the field of medical imaging, medical image computing focuses on the computational analysis of the images, not their acquisition. The methods can be grouped into several broad categories: image segmentation, image registration, image-based physiological modeling, and others. (Search "medical image computing" on Wikipedia.com June 24, 2021. CC-BY-SA 3.0 Modified. Accessed June 24, 2021.) Medical image computing may include one or more processors or controllers on one or more computing devices. Such processors or controllers may be referred to herein as medical image processors. Medical imaging and medical image computing together can provide systems and methods to image, quantify and fuse both structural and functional information about a patient in vivo. These two technologies include the transformation of computational models to represent specific subjects/patients, thus paving the way for personalized computational models. Individualization of generic computational models through imaging can be realized in three complementary directions: definition of the subject-specific computational domain (anatomy) and related subdomains (tissue types); definition of boundary and initial conditions from (dynamic and/or functional) imaging; and characterization of structural and functional tissue properties. Medical imaging and medical image computing enable in the translation of models to the clinical setting with both diagnostic and therapeutic applications. (Id.) In certain embodiments, medical image computing can be used to generate a bone model, a patient specific model, and/or a patent specific instrument from medical imaging and/or medical imaging data.
Notes
Added by DJM 2 2022
Raw Data
<w:p w14:paraId="33C2CB88" w14:textId="5190ED7A" w:rsidR="004D60A7" w:rsidRPr="00A1491D" w:rsidRDefault="004D60A7" w:rsidP="006612DC"><w:pPr><w:pStyle w:val="NumberedParagraph"/><w:tabs><w:tab w:val="clear" w:pos="360"/><w:tab w:val="num" w:pos="1080"/></w:tabs><w:rPr><w:rFonts w:asciiTheme="minorHAnsi" w:hAnsiTheme="minorHAnsi"/></w:rPr></w:pPr><w:r w:rsidRPr="00A1491D"><w:rPr><w:rFonts w:asciiTheme="minorHAnsi" w:hAnsiTheme="minorHAnsi"/></w:rPr><w:t xml:space="preserve">As used herein, "medical image computing" or "medical image processing" refers to systems, software, hardware, components, and/or apparatus that involve and combine the fields of computer science, information engineering, electrical engineering, physics, mathematics and medicine. Medical image computing develops computational and mathematical methods for working with medical images and their use for biomedical research and clinical care. One goal for medical image computing is to extract clinically relevant information or knowledge from medical </w:t></w:r><w:r w:rsidRPr="00A1491D"><w:rPr><w:rFonts w:asciiTheme="minorHAnsi" w:hAnsiTheme="minorHAnsi"/></w:rPr><w:lastRenderedPageBreak/><w:t xml:space="preserve">images. While closely related to the field of medical imaging, medical image computing focuses on the computational analysis of the images, not their acquisition. The methods can be grouped into several broad categories: image segmentation, image registration, image-based physiological modeling, and others. (Search "medical image computing" on Wikipedia.com June 24, 2021. CC-BY-SA 3.0 Modified. Accessed June 24, 2021.) Medical image computing may include one or more processors or controllers on one or more computing devices. Such processors or controllers may be referred to herein as medical image processors. Medical imaging and medical image computing together can provide systems and methods to image, quantify and fuse both structural and functional information about a patient in vivo. These two technologies include the transformation of computational models to represent specific subjects/patients, thus paving the way for personalized computational models. Individualization of generic computational models through imaging can be realized in three complementary directions: definition of the subject-specific computational domain (anatomy) and related subdomains (tissue types); definition of boundary and initial conditions from (dynamic and/or functional) imaging; and characterization of structural and functional tissue properties. Medical imaging and medical image computing enable in the translation of models to the clinical setting with both diagnostic and therapeutic applications. (Id.) In certain embodiments, medical image computing can be used to generate a bone model, a patient specific model, and/or a patent specific instrument from </w:t></w:r><w:r w:rsidR="00A13F68" w:rsidRPr="00A1491D"><w:rPr><w:rFonts w:asciiTheme="minorHAnsi" w:hAnsiTheme="minorHAnsi"/></w:rPr><w:t>medical imaging and/or medical imaging data.</w:t></w:r></w:p>
Submit