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114 results about "Lung squamous cell carcinoma" patented technology

Method for distinguishing between head and neck squamous cell carcinoma and lung squamous cell carcinoma

The present invention is a method distinguishing between head and neck squamous cell carcinoma and lung squamous cell carcinoma. In particular, a 10-gene classifier has been identified which can be used to distinguish between primary squamous cell carcinoma of the lung and metastatic head and neck squamous cell carcinoma. These genes include CXCL13, COL6A2, SFTPB, KRT14, TSPYL5, TMP3, KLK10, MMP1, GAS1, and MYH2. A panel of one or more of these genes, or proteins encoded thereby, can be used for early diagnosis and selection of an appropriate therapeutic treatment.
Owner:WISTAR INST THE A CORP OF PA +1

Non-small cell lung cancer pathological section identification method based on deep convolutional neural network

The invention discloses a non-small cell lung cancer pathological section identification method based on a deep convolutional neural network. The method comprises the following steps: acquiring pathological sections of non-small cell lung cancer in a public data set from TCGA; constructing a deep learning model for training; inputting the training data set into a convolutional neural network for training to obtain a learned convolutional neural network model; and inputting the training data set into a convolutional neural network for training to obtain a learned convolutional neural network model. According to the method, the Inception-v3 model and the CBAM attention mechanism are fused together, so that the classification of the non-small cell lung cancer is realized, and the network precision is improved through the attention mechanism; meanwhile, a deep convolutional neural network Inception-v3 experimental result shows that the non-small cell lung cancer pathological section identification method based on deep learning provided by the invention can effectively classify lung adenocarcinoma and lung squamous cell carcinoma, reduces the burden of doctors to a certain extent, and realizes very good performance in the field of medical image identification.
Owner:LIAONING TECHNICAL UNIVERSITY

Lung cell pathology rapid on-site evaluation system and method and computer readable storage medium

PendingCN111489833ASolve the problem that pathological diagnosis results cannot be obtained immediatelyImprove diagnostic efficiencyCharacter and pattern recognitionNeural architecturesMicroscopic imageCurrent cell
The invention provides a lung cell pathology rapid on-site evaluation system and method and a computer readable storage medium, which are used for rapidly evaluating a cell sample on an operation site. The lung cell pathology rapid on-site evaluation system comprises a microscopic image acquisition device which comprises an objective table used for bearing a lung cell sample and a camera used forshooting the cell sample to obtain a microscopic image of the sample; an image evaluation device with a neural network classification model used for classifying the microscopic images, wherein the obtained classification result is one of lung squamous cell carcinoma, lung adenocarcinoma, small cell lung cancer, unclear non-small cell lung cancer, other malignant lesions, no obvious abnormality, granuloma and inflammation; and an output device connected to the image evaluation device and used for outputting the classification result to a user. According to the invention, the neural network classification model is used for evaluating the microscopic image acquired by the microscopic image acquisition device, and an evaluation result is obtained on an operation site, so that the problems thatthe current cell pathological diagnosis is complex and time-consuming, and the pathological diagnosis result cannot be obtained immediately are solved, and the diagnosis efficiency is effectively improved.
Owner:SHANGHAI XINGMAI INFORMATION TECH CO LTD

Lung gland squamous cell carcinoma diagnosis device based on PET/CT image sub-region imaging omics characteristics

The invention discloses a lung glandular squamous cell carcinoma diagnosis device based on PET / CT image subarea imaging omics characteristics, and belongs to the field of medical images. The diagnosisdevice comprises: a voxel three-dimensional feature extraction module, which is used for extracting a CT local main gradient angle feature value of each voxel of a lung tumor in a neighborhood in a PET / CT image, a CT value of the voxel and a PET value, and forming a three-dimensional feature vector of the voxel; a feature clustering module used for clustering the obtained three-dimensional feature vector of each voxel to obtain a tumor sub-region partition; a radios image omics feature extraction module used for extracting radios image omics features of each tumor sub-region in a partitioningmanner; and a classification module used for distinguishing whether the tumor is lung squamous cell carcinoma or lung adenocarcinoma according to the extracted radiomics characteristics of the radiomics. According to the diagnosis device, the heterogeneity in the tumor is better considered, and the accuracy of tumor diagnosis is effectively improved by extracting more effective imaging omics characteristics.
Owner:ZHEJIANG LAB +1

System for predicting prognosis of patient with lung squamous cell carcinoma

ActiveCN106442990AAccurately predict clinical prognosisImproving the level of prognosis predictionBiological material analysisSquamous CarcinomasSOX2
The invention discloses a system for predicting the prognosis of a patient with lung squamous cell carcinoma. The system includes a subsystem for detecting the expression quantity of such five proteins as EGFR, p38alpha, AKT1, SOX2 and E-cadherin and a protein expression quantity data processing system. The subsystem for detecting the expression quantity of the five proteins is allowed to measure the expression quantity of the proteins through an immunohistochemistry staining method; the protein expression quantity data processing system is allowed to convert the expression quantity of the five proteins from the squamous cell carcinoma tissues separated from the patient with the lung squamous cell carcinoma to a prognostic score; based on the prognostic score, the prognosis of a patient with the lung squamous cell carcinoma is predicted.
Owner:BIOMEDICAL ANALYSIS CENT OF ACADEMY OF MILITARY MEDICAL SCI

Method for detecting lung cancer typing

The invention provides a method for diagnosing and predicting lung cancer typing, wherein the method comprises the following steps: (1) exciting normal tissues, paracancerous tissues or cancer lesiontissues of a patient lung by exciting light with the wave length of 440-700 nm; (2) receiving spontaneous fluorescent light with the wave length of 460-800 nm; and (3) analyzing the intensity and / or fluorescence distribution pattern chart of spontaneous fluorescent light, and identifying adenocarcinoma or adenosquamous carcinoma of lung.
Owner:SHANGHAI JIAO TONG UNIV
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