Anumana, Inc.

Deepak Anand

Rakesh Barve

Animesh Agarwal

Karthik K Bharadwaj

Yogisha Heggadahalli Jayendra

Sughosh Indurkar

Murali Aravamudan

Suthirth Vaidya

Rohit Jain

Arjun Puranik

Abhijith Chunduru

Sai Saketh Chennamsetty

Apparatus and method for object pose estimation are disclosed. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to receive a plurality of sets of echo data, wherein the plurality of sets of echo data is configured for generation of a plurality of echo depth maps, segment the plurality of echo depth maps, determine a depth datum related to pixels of an object of interest as a function of the plurality of segmented echo depth maps, generate a three dimensional (3D) point cloud related to the object of interest as a function of the depth datum and generate a pose datum of the object of interest as a function of the 3D point cloud.

Apparatus and method for object pose estimation in a medical image

A system for determining position signals of electrodes using a retrained machine-learning model includes at least a catheter including a plurality of electrodes configured to collect a plurality of potential signals and a magnetic sensor configured to collect magnetic data, and at least a computing device including a memory. The processor receives a first training set, wherein the first training set includes patient-agnostic data; receives a second training set, wherein the second training set includes patient-specific data, trains a mapping machine-learning model using the first training set, retrains the mapping machine-learning model using the second training set, receives at least a first signal, wherein the first signal includes a potential signal of the plurality of potential signal and the magnetic data, and generates, using the retrained machine-learning model, as a function of the at least a first signal, a first position signal for an electrode of the plurality of electrodes.

Methods and systems for determining position signals of electrodes using a retrained machine-learning model

An apparatus for the generation of an impedance model of a biological chamber is disclosed. The apparatus includes a catheter assembly comprising a plurality of electrodes arranged into one or more constraint pairs. The apparatus includes a processor and a memory communicatively connected to the processor. The memory instructs the processor to receive tank data. The memory instructs the processor to generate a plurality of relative configurations of the plurality of electrodes as a function of the tank data using a compliant configuration generator. The memory instructs the processor to record voltage data from the plurality of electrodes within a biological chamber as a function of the plurality of relative configurations. The memory instructs the processor to map a plurality of impedance metrics for each relative configuration as a function of the voltage data. The memory instructs the processor to generate an impedance model as a function of the map.

Apparatus and a method for the generation of an impedance model of a biological chamber

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Doddanekundi, India

Deepak Anand