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47 results about "Pituitary tumors" patented technology

Abnormal, noncancerous growth that develops in the pituitary gland.

Chinese medicine composition for treating pituitary tumor and application of Chinese medicine composition

The invention relates to a Chinese medicine composition for treating pituitary tumor, which is prepared from the following bulk pharmaceutical chemicals in parts by weight: 15-25 parts of arisacma consanguineum, 10-20 parts of seaweed, 25-35 parts of raw oyster, 4-14 parts of ginger processed pinellia, 7-17 parts of rhizoma sparganii, 10-20 parts of salvia chinensis, 7-17 parts of poria cocos and25-35 parts of raw astragalus mongholicus. The invention also provides an application of the Chinese medicine composition. The Chinese medicine composition has the advantages that the compatibility of the Chinese medicine composition conforms to the assistant and guide principle of the traditional Chinese medicine. The clinical test proves that the Chinese medicine composition disclosed by the invention has obvious curative effect advantages, and has good curative effect on eliminating pituitary tumor, lowering the postoperative recurrence rate and reducing side effect after the western medicine is taken. The Chinese medicine composition also has good curative effect, no obvious toxic or side effect, no adverse reaction and wide clinic application prospect.
Owner:YUEYANG INTEGRATED TRADITIONAL CHINESE & WESTERN MEDICINE HOSPITAL SHANGHAI UNIV OF CHINESE TRADITIONAL MEDICINE

Pituitary tumor image classification method, pituitary tumor image classification system and electronic equipment

The embodiments of the application discloses a pituitary tumor image classification method, a pituitary tumor image classification system and electronic equipment. The method comprises the following steps: acquiring a magnetic resonance image of a brain to be classified; inputting the magnetic resonance image of the brain to be classified into a classification model, wherein the classification model is an artificial neural network comprising an attention module, and the classification model is obtained after training by taking the extracted magnetic resonance images form the area where the pituitary tumor is located as a first training sample; extracting image features in the magnetic resonance image of the brain through the classification model, determining the importance degree of each image feature in the the magnetic resonance image of the brain through the attention module, and obtaining a classification result corresponding to the magnetic resonance image of the brain based on the importance degree of each image feature. By implementing the embodiment of the invention, the importance degree of the image feature can be determined through the attention module according to the contribution of each image feature to the classification task, so that the classification accuracy is improved.
Owner:SUN YAT SEN UNIV CANCER CENT

Pituitary tumor texture image grading method based on fine-grained medical image segmentation and true value discovery data amplification

The invention discloses a pituitary tumor texture image grading method based on fine-grained medical image segmentation and true value discovery data amplification. The pituitary tumor texture image grading method comprises the following steps: 1, optimizing fruit fly-density peak clustering medical image segmentation based on fine granularity; 2, amplifying pituitary adenoma data discovered on the basis of true values; and 3, grading based on the pituitary adenoma texture images in the step 1 and the step 2. According to the pituitary tumor texture image grading method, the medical image is accurately segmented through fusion of a fine-grained division algorithm and an FOA-DPC algorithm; medical image data amplification based on a true value discovery theory is also realized, and the problem of few available medical image data sets is solved. The pituitary tumor texture image grading method combines a KFOA-DPC segmentation algorithm with deep learning, so as to solve the problems thatthe gray scale of a dicom format image is numerous and jumbled, and features are not easy to extract, realize classification of pituitary adenoma texture softness and toughness and assist clinical diagnosis.
Owner:XUZHOU MEDICAL UNIV

A device for cutting and removing pituitary tumors

The invention discloses a pituitary tumour cutting and clearing-away device. The pituitary tumour cutting and clearing-away device comprises an external clearing-way machine, a drainage tube and a sucking mechanism, wherein the external clearing-away machine is connected to the drainage tube; a negative-pressure suction machine is started; the drainage tube is used for guiding and draining pituitary tumours into a tumour substance collecting box; a sucking head sucks pituitary tumours; after last-time sucking is finished, the sucking tube is pulled upwards, so that extrusion force, on elastictelescopic plates at two sides, of the sucking tube disappears, the elastic telescopic plates at the two sides are shrunk to be closed in a contact mode, and therefore, the drainage tube is preventedfrom generating reflow to make sucked pituitary tumours flow back, the sucking head is prevented from being exposed in air for a long term to be infected with bacteria, and possibility of bacterial infection in operation is reduced; when the sucking mechanism is used again, the sucking tube is downwards extruded, so that two side walls of the sucking tube cling to the elastic telescopic plates, and the sucking head passes through a tube orifice to suck the pituitary tumours; the sucking head adopts a flat tube body, and the inner cavity of the sucking head is gradually reduced from back to front, and a formed liquid knife is more sharp, so that practicability of the device is improved.
Owner:WEST CHINA HOSPITAL SICHUAN UNIV

Artificial intelligence technology-based pituitary tumor operation planning system

The invention discloses a pituitary tumor operation planning system based on an artificial intelligence technology. The system comprises the following steps: 1, acquiring a vascular medical image sequence, a skeleton medical image sequence and a pituitary tumor medical image sequence; 2, if the medical image sequences are the image sequences shot at different moments or the image sequences shot at the same moment are not in the same coordinate system, performing registration, and placing the image sequences in the same coordinate system; 3, using a deep neural network model to take each medical image sequence in the same coordinate system as input, and outputting a blood vessel image segmentation result, a skeleton image segmentation result and a pituitary tumor image segmentation result; and 4, performing three-dimensional reconstruction on the blood vessel image segmentation result, the skeleton image segmentation result and the pituitary tumor image segmentation result to obtain a three-dimensional model for pituitary tumor preoperative planning. The method is high in processing speed and high in reliability, so that preoperative evaluation and surgical planning of clinicians become simple, accurate and rapid.
Owner:上海寻是科技有限公司
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