14 results about "Bone Marrow Smear" patented technology

This application relates to the field of molecular pathology diagnostic technology, specifically disclosing a bone marrow smear FISH detection kit and its application. The kit includes a rapid hybridization buffer, a stabilization pretreatment solution, room temperature hybridization probes, probe dilution buffer, low-salt washing buffer, high-salt washing buffer, counterstaining solution, positive control samples, and negative control samples. The room temperature hybridization probes include broken probe pairs targeting the BCR-ABL, PML-RARA fusion genes, and IgH gene rearrangements. The detection method of this kit includes sample pretreatment, probe denaturation, room temperature hybridization, washing and counterstaining, and signal interpretation. Through the synergistic effect of the rapid hybridization buffer and the short-chain low-Tm value probes, rapid hybridization at room temperature is achieved, eliminating the need for a dedicated isothermal hybridization instrument. The stabilization pretreatment solution can complete cell permeation and RNA removal in one step, resulting in a high degree of operational standardization.

The invention relates to the crossing field of medical image processing and artificial intelligence technology, in particular to a bone marrow cell morphology artificial intelligence analysis method and system, and the method comprises the steps: obtaining a multi-view high-resolution image of a bone marrow smear and / or a peripheral blood smear under the oil immersion magnification, and carrying out the preprocessing; carrying out red blood cell coarse segmentation and fine classification through a cascade deep network, and identifying target-shaped, broken, teardrop-shaped and elliptical red blood cells; correcting broken red blood cell counting by adopting a fragment aggregation correction algorithm; and calculating an MCI value in combination with blood routine test data, and carrying out weighted fusion on the MCI value and the abnormal red blood cell proportion to generate a thalassemia screening comprehensive score. Therefore, the problems of low manual identification efficiency, insufficient abnormal red blood cell identification accuracy, large broken red blood cell counting deviation, difficulty in distinguishing multiple types of abnormal red blood cells, lack of organic combination with clinical diagnosis indexes and the like are solved, and the efficiency and accuracy of morphological analysis of bone marrow cells are improved; and a reliable basis is provided for diagnosis of diseases such as thalassemia.

This invention discloses a slide degreasing mechanism for a bone marrow smear scanner, comprising a base plate, a base plate, and a control device. The base plate has an opening for the robotic arm to grip the slide and quickly pass it to the slide wiping position. The base plate also includes a feeding roll, a feeding device, a receiving sensing component, a receiving roll, and a receiving device. The receiving sensing component includes a rotation positioning plate, a rotating shaft, a limit switch mounting plate, a limit switch, and a sensing rod. During the degreasing operation, after the sensing rod determines that the wiping cloth is taut, the robotic arm sends the slide to the wiping position. The feeding device delivers the wiping cloth and covers it, allowing the wiping cloth to be in a relaxed state for degreasing. Simultaneously, the rotation positioning plate rotates downwards. After a limited time, the receiving component tightens the wiping cloth, causing it to rotate upwards until the limit switch is triggered, ending the receiving process. This invention enables fully automated oil removal, ensuring rapid and effective removal of immersion oil from slides without damaging cells, saving manpower and time, and thus enabling faster cleaning of slides after bone marrow smear scanning.

The invention provides a preparation method of an experimental animal bone marrow smear, and belongs to the technical field of hematological examination. According to the invention, a specific smear method is matched with homologous serum, so that the mechanical damage of bone marrow cells in the collection and smear preparation process can be obviously reduced, and the phenomena of excessive crushing and uneven distribution of the cells are effectively avoided, so that the high-quality bone marrow smear with complete cell morphology and clear background is prepared; therefore, the morphological observation effect and the reading success rate of the bone marrow cells are directly improved, reliable technical guarantee is provided for accurately evaluating the influence of the test substance on the hematopoietic function of the animal in non-clinical toxicity research, and the accuracy and repeatability of experimental results are enhanced.

The utility model relates to a kind of bone marrow biopsy and smear transfer double-cavity integrated box, including box and box cover, first chamber and second chamber not interconnected are equipped in the box, the smear rack for supporting smear is equipped in the first chamber, the bottle rack for supporting screw neck bottle is equipped in the second chamber, the adsorption component for adsorbing formaldehyde is equipped in the second chamber.This application sets up first chamber and second chamber not interconnected in box, smear rack is set in first chamber for supporting smear, bottle rack is set in second chamber for supporting screw neck bottle, smear and screw neck bottle containing bone marrow specimen and formalin solution are stored separately for transfer, formalin volatilization cannot cause bone marrow smear to fumigate and dye, there is no fumigation and cross-contamination risk between biopsy specimen and smear, ensure the accuracy of subsequent diagnostic results, volatilized formaldehyde is adsorbed by adsorption component, can avoid that formaldehyde is absorbed by medical staff by diffusion, and safety is high.

The present invention is directed toward an apparatus for producing consistent blood and bone marrow smears. The apparatus may include a smearer configured to receive a planar smear slide. The smearer may include an angled portion that comes into contact with the planar smear slide and creates the smear. The apparatus operates by allowing users of all skill levels to prepare a blood or bone marrow smear sample.

The invention provides a bone marrow smear-based AML standard chemotherapy primary refractory risk prediction method and device. The method comprises the following steps: acquiring a bone marrow smear digital image of an AML patient, processing the bone marrow smear digital image by using an image analysis model to extract morphological characteristics of a cell ecosystem, inputting the morphological characteristics of the cell ecosystem into a TP53 drug resistance estimation model, and estimating the drug resistance of TP53 according to an output result of the TP53 drug resistance estimation model. And predicting whether the primary refractory risk of the TP53 mutant AML of the AML patient is a suspected high risk or not, and outputting prompt information suggested to carry out TP53 gene precise molecular detection under the condition that the primary refractory risk of the TP53 mutant AML of the AML patient is the suspected high risk. Therefore, for a low-risk AML patient, the possibility of TP53 gene precise molecular detection is reduced, the efficiency of predicting the original refractory risk can be improved on the whole, and the problems in the prior art are solved.

The utility model discloses a bone marrow smear dyeing device which comprises a controller, a connecting line, a dyeing table and an adjusting assembly, smear dyeing adjustment is performed through the adjusting assembly, a rack plate, an adjusting gear and a micro motor dyeing assembly, so that multiple groups of smears can perform synchronous dyeing operation, and the bone marrow smear dyeing efficiency is improved; the multiple sets of obliquely-arranged containing grooves formed in the inner side of the containing box are matched with the thick blood film, the thin blood film and the marking area to assist in improving the dyeing efficiency of the bone marrow smear.

The invention provides an MDS malignant transformation risk assessment method based on machine learning and bone marrow cell morphology, and the method comprises the steps: S101, building a myelodysplastic syndrome (MDS) malignant transformation risk assessment model based on bone marrow morphology cell characteristics; s102, acquiring a bone marrow smear image of the MDS patient, identifying the bone marrow smear image, obtaining proportion data of the target type of bone marrow cells, and recording the proportion data as bone marrow cell type proportion data; s103, inputting the bone marrow cell type proportion data into an MDS malignant transformation risk assessment model, and calculating and outputting a risk assessment score of transformation from MDS to acute myelogenous leukemia (AML) of the patient; and S104, the patients are grouped according to the risk assessment scores, and a treatment scheme is recommended. The method has the advantages that the basic level is easy to obtain, the needed economic cost is low, calculation is convenient and the like, medical personnel can be assisted in optimizing treatment decisions, and the survival rate of high-risk patients is improved.

The utility model relates to the technical field of blood smears, in particular to a blood and bone marrow smear device. The slide clamping device is composed of an operation table, a slide clamping device and a slide pushing clamping unit. A sliding rail, an electric push rod and an operation part are arranged on the operation table. The electric push rod can accurately control the position and speed, and the operation part can set parameters and be started to achieve horizontal movement of the dovetail groove. The slide clamping device is used for fixing a slide through a glass carrying table, a limiting block, a sliding block and a spring. The push piece adjusting device comprises a lifting sliding table, an angle adjusting unit and a push piece clamping unit. The height of the lifting sliding table is adjusted through a helical gear and a helical rack, the angle adjusting unit can adjust the angle of the push piece, and the push piece clamping unit clamps or loosens the push piece through a clamping groove and a rotating piece. All parts of the smear device are matched with one another, blood and bone marrow smear operation is facilitated, the structure is exquisite, and operation is convenient and fast.

The invention discloses a plasma cell morphological multiple myeloma and AL amyloidosis identification method, and relates to the technical field of medical detection.The method comprises the steps that an original digital image of a bone marrow smear is obtained, image processing is carried out, plasma cell segmentation data is generated, and the original digital image of the bone marrow smear is obtained; the plasma cell segmentation data is used for identifying plasma cell regions of a plurality of plasma cells and cell nucleus regions of the plasma cells, calculating morphological parameters of each of the plurality of plasma cells to generate a feature data set, the morphological parameters comprising a nucleus-plasma ratio and nucleus roundness, inputting the feature data set to an identification classification model, and outputting an identification result, the identification result comprises multiple myeloma, AL amyloidosis and no disease. According to the method, the nuclear-level morphological characteristics of the plasma cells are extracted through automatic image segmentation, and classification is performed by using the convolutional neural network model optimized by transfer learning, so that the problems of high subjectivity and low efficiency of a traditional diagnosis method are solved, and rapid and high-precision automatic identification of multiple myeloma and AL amyloidosis is realized.

The application discloses a kind of marrow megakaryocyte automatic detection and counting method, system and medium, the present application method includes the local image obtained by segmenting marrow smear panorama image carries out cell filtering and extracts cell boundary box set;Active sample selection is generated to cell boundary box set guide mask;Under the guidance of guide mask, sample active screening is carried out;Pre-training mask auto-encoder MAE is obtained based on the image sample of active screening;The encoder weight of pre-trained mask auto-encoder MAE is introduced into marrow megakaryocyte detection classification model based on mask auto-encoder MAE, and marrow megakaryocyte detection classification model is trained end to end to be used to realize marrow megakaryocyte detection and counting of marrow megakaryocyte image data set of target domain T.The present application aims to realize marrow megakaryocyte automatic identification, solve marrow megakaryocyte interclass imbalance problem, improve the classification precision and recognition ability of marrow megakaryocyte.

The application relates to a DLBCL tumor cell intelligent detection method and system in bone marrow smears, which comprises the following steps: acquiring a full-field digital pathology image of a bone marrow smear; performing overlapping block processing to obtain a plurality of sub-image blocks; performing region of interest screening on the sub-image blocks to retain ROI image blocks containing effective cells; performing standardization processing on the ROI image blocks to obtain a target detection input image; detecting the target detection input image by using a deep learning target detection model to output a bounding box target containing DLBCL tumor cells and other cells; performing edge filtering processing on the bounding box target to eliminate the bounding box corresponding to the edge incomplete cells; counting the number of DLBCL tumor cells and other cells; calculating the proportion of DLBCL tumor cells in all nucleated cells to output a detection result. The application realizes automatic identification and quantitative analysis of DLBCL cells, has small calculation overhead, and has a high recognition rate for cross-block cells.

The application provides a whole bone marrow smear automatic counting method and system based on a visual large model and self-supervised learning. An ROI segmentation model is used to segment an interested region from the bone marrow smear. A TOI classification model is used to cut a slice from the bone marrow smear corresponding to the interested region, and perform binary classification to select an interested slice. A cell segmentation model based on the visual large model is used to segment all cells on the interested slice. A cell classification model based on the self-supervised learning is used to classify the cells, and finally counting is performed. The application has strong generalization and high accuracy, and can provide valuable reference for pathologists of various medical centers.