公开(公告)号：US20230408413A1

公开(公告)日：2023-12-21

申请号：US18334186

申请日：2023-06-13

Applicant: Applied Materials, Inc.

Inventor： Viswanath BAVIGADDA ,  Shubhayan BHATTACHARYA ,  Tapashree ROY ,  Ankur KADAM ,  Kiran Rangaswamy AATRE ,  Suraj RENGARAJAN

IPC: G01N21/64 ,  G01N21/39

CPC classification number: G01N21/6456 ,  G01N21/643 ,  G01N21/39 ,  G01N2021/399 ,  G01N2201/0633 ,  G01N2201/1235 ,  G01N21/94

Abstract: In one embodiment, an apparatus to identify chemical and spatial properties of nanoparticles in a semiconductor cleaning solution, comprises a broadband light source to provide an excitation beam; a focusing lens in a path of the excitation beam to form a focused excitation beam; a sample cell, the sample cell configured to hold a cleaning solution and one or more insoluble analytes-of-interest therein; a plurality of optical lens in the path of one or more fluorescence signals to focus the one or more fluorescence signals; and an imaging device, wherein the imaging device captures the one or more fluorescence signals to form a plurality of images that contain both spatial data and spectral data about the one or more insoluble analytes-of-interest.

公开(公告)号：US20240037740A1

公开(公告)日：2024-02-01

申请号：US18360074

申请日：2023-07-27

Applicant: Applied Materials, Inc.

Inventor： Sumit Kumar JHA ,  Gursewak SINGH ,  Rithika CARIAPPA ,  Kiran Rangaswamy AATRE

IPC: G06T7/00 ,  G06V10/82 ,  G06V10/26 ,  G16H50/30

CPC classification number: G06T7/0012 ,  G06V10/82 ,  G06V10/267 ,  G16H50/30 ,  G06T2207/30024 ,  G06T2207/10056 ,  G06T2207/30068 ,  G06T2207/10024

Abstract: Methods and systems for generating a predictive HER2 score using machine learning models are disclosed. An example method generally includes identifying a plurality of nuclei and membrane segments in regions of interest in an input image using a first machine learning model. For the plurality of nuclei and membrane segments identified in the input image, a plurality of features are extracted and classified into one of a plurality of feature categories. Using a second machine learning model, a predictive HER2 score indicating the likelihood of whether a stained tissue sample captured in the input image is HER2 positive or HER2 negative is generated based on the classification assigned to the plurality of extracted features associated with the plurality of segments.

公开(公告)号：US20230162354A1

公开(公告)日：2023-05-25

申请号：US17993144

申请日：2022-11-23

Applicant: Applied Materials, Inc.

Inventor： Tapashree ROY ,  Shubhayan BHATTACHARYA ,  Kiran Rangaswamy AATRE ,  Sumit Kumar JHA ,  Suraj RENGARAJAN ,  Riya DUTTA

IPC: G06T7/00 ,  G06V10/26 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06T7/0012 ,  G06V10/26 ,  G06V10/764 ,  G06V10/82 ,  G06T2207/10036 ,  G06T2207/30024

Abstract: According to certain embodiments, a system for detection of anomalous cells, comprises a hyperspectral imaging system; a memory having executable instructions stored thereon; and a processor configured to execute the executable instructions to cause the system to: receive a patient hyperspectral image comprising a pixel spectral signature for each pixel of the received patient hyperspectral image; classify the patient hyperspectral image by a machine learning model trained to classify hyperspectral images based on pixel spectral signatures; and provide an indication that the patient hyperspectral image contains an anomalous cell type, responsive to the classifying.