公开(公告)号：US11781914B2

公开(公告)日：2023-10-10

申请号：US17687170

申请日：2022-03-04

申请人： Sivananthan Laboratories, Inc.

发明人： Nigel Browning ,  Christopher Frank Buurma

IPC分类号： G01J5/22 ,  H04N5/33 ,  G01J5/20

CPC分类号： G01J5/22 ,  H04N5/33 ,  G01J2005/202

摘要： An imaging system includes a focal plane array, readout electronics, and a computing system in which the number of active pixels is either set at a low-fraction of the total pixels thereby reducing the effect of radiation damage, or radiation damage over time is detected and automatically compensated. Machine learning is used to identify radiation damaged pixels and damaged regions which are subsequently eliminated and replaced by the computational system. The machine learning is used to identify changes in the fixed pattern signal/noise and/or noise of the system, and is then computationally corrected.

公开(公告)号：US20220343497A1

公开(公告)日：2022-10-27

申请号：US17687310

申请日：2022-03-04

申请人： Sivananthan Laboratories, Inc.

发明人： Christopher Frank Buurma

IPC分类号： G06T7/00 ,  H04N5/33 ,  A61B5/00 ,  A61B5/01

摘要： An apparatus and method to assist making treatment decisions for burn injuries. The apparatus will leverage computational imaging methodologies with conventional thermographic analysis techniques. Using infrared sensors, computational image analysis, and burn assessment using thermographic imaging, a complete burn assessment imaging device can be fabricated entirely from commercially-available components. This device will use advanced software paired with a smartphone-mounted infrared camera to perform a detailed thermographic analysis using a burn triage algorithm.

公开(公告)号：US20220333996A1

公开(公告)日：2022-10-20

申请号：US17687170

申请日：2022-03-04

申请人： Sivananthan Laboratories, Inc.

发明人： Nigel Browning ,  Christopher Frank Buurma

IPC分类号： G01J5/22 ,  H04N5/33

摘要： An imaging system includes a focal plane array, readout electronics, and a computing system in which the number of active pixels is either set at a low-fraction of the total pixels thereby reducing the effect of radiation damage, or radiation damage over time is detected and automatically compensated. Machine learning is used to identify radiation damaged pixels and damaged regions which are subsequently eliminated and replaced by the computational system. The machine learning is used to identify changes in the fixed pattern signal/noise and/or noise of the system, and is then computationally corrected.