Abstract: Brushes for cleaning wafers after a Chemical Mechanical Polishing (CMP) process and methods for fabricating such brushes are provided. An exemplary method for fabricating a brush for cleaning wafers after a Chemical Mechanical Polishing (CMP) process includes forming a brush configured for contacting the wafers; and, while forming the brush, controlling formation of pores within the brush to a maximum pore dimension, wherein the maximum pore dimension is 1000 nanometers (nm).

Abstract: An image processing method comprises: acquiring a plurality of images, wherein display content of the images comprises at least a monitoring region of a target part of an object to be monitored; performing semantic segmentation on the images to obtain a first region feature of the monitoring region in the images; determining a second region feature of the monitoring region based on a dependency relationship between a plurality of pre-constructed prototypes and the first region feature, wherein different prototypes are used to represent different types of monitoring regions; and identifying feature information of the monitoring region based on the first region feature and the second region feature to determine an identification result of the monitoring region. The present application solves the technical problem of low identification accuracy when identifying images to be monitored in related art.

Abstract: An method for detecting a target substance includes providing a sample including the target substance and an active species, converting the active species into a deactivated species, adding a reactive agent into the sample to form a solid species including the target substance, separating the solid species from the deactivated species by solid-liquid separation, and determining a concentration of the target substance in the sample by measuring a concentration of the target substance in the solid species.

Abstract: A method, an apparatus, and a non-transitory computer readable medium for training an image processing model are provided. The method includes: acquiring a sample image comprising a target object to determine an object segmentation image of the target object in the sample image; constructing an object coordinate map corresponding to the object segmentation image according to the object segmentation image; and training an image processing model comprising a self-attention mechanism layer according to the sample image, the object segmentation image, and the object coordinate map.

Abstract: An image processing method is provided. The method includes obtaining a to-be-processed image comprising a target object, and inputting the to-be-processed image to a convolutional layer of an image processing model, to obtain an initial feature map of the to-be-processed image, wherein the image processing model comprises an encoder and a decoder; inputting the initial feature map to a self-attention mechanism layer of the encoder, and obtaining a target feature map corresponding to the initial feature map according to position information of each feature in the initial feature map and a position relationship between the each feature and other features; and inputting the target feature map to the decoder for processing, to obtain an object segmentation map and an object label of the target object in the to-be-processed image.

Abstract: Tools and brushes for cleaning wafers after a Chemical Mechanical Polishing (CMP) process and methods for fabricating such brushes are provided. A brush for cleaning wafers after a Chemical Mechanical Polishing (CMP) process includes a sleeve member; and a plurality of spaced-apart nodules disposed to protrude from the sleeve member, and wherein an outer surface of the nodules is formed by a porous polymeric material having pores, and wherein the pores have a maximum pore dimension of 1000 nanometers (nm).

Abstract: A bottom-fillable spray bottle is provided, it includes a bottle body, a liquid spraying assembly, a vent assembly and a liquid injection assembly. The liquid injection assembly includes a liquid inlet nozzle and a bayonet. The liquid injection assembly is arranged at an opening of a bottle bottom, and the bayonet can releasably seal the opening. The bayonet is provided with a first and a third liquid inlet channel. When pushing a part of the bayonet into the opening so that the third liquid inlet channel enters the opening and enables the third liquid inlet channel to be above the opening, the channels and the accommodating cavity are communicated with each other, and when the bayonet seals the opening, the third liquid inlet channel and the accommodating cavity are not communicated with each other. The ejector pin with a first sealing ring can releasably seal the bottle body.

Abstract: A method of opportunistic screening of osteoporosis includes obtaining a plain film chest X-ray (CXR); extracting regions of interest (ROIs) from the plain film CXR; and providing individual bone mineral density (BMD) scores corresponding to the extracted ROIs and a joint BMD corresponding to the plain film CXR based on a multi-ROI model by performing: inputting the extracted ROIs into a backbone network to generate individual feature vectors, each individual feature vector corresponding to one of the extracted ROIs; concatenating the individual feature vectors into a joint feature vector; individually decoding the individual feature vectors by a shared fully connected (FC) layer to generate the individual BMDs, each individual BMD corresponding to one of the individual feature vectors; and decoding the joint feature vector by a separate FC layer to generate the joint BMD.

Abstract: Brushes for cleaning wafers after a Chemical Mechanical Polishing (CMP) process and methods for fabricating such brushes are provided. An exemplary method for fabricating a brush for cleaning wafers after a Chemical Mechanical Polishing (CMP) process includes forming a brush configured for contacting the wafers; and, while forming the brush, controlling formation of pores within the brush to a maximum pore dimension, wherein the maximum pore dimension is 1000 nanometers (nm).

Abstract: A bottom-fillable spray bottle is provided, it includes a bottle body, a liquid spraying assembly, a vent assembly and a liquid injection assembly. The liquid injection assembly includes a liquid inlet nozzle and a bayonet. The liquid injection assembly is arranged at an opening of a bottle bottom, and the bayonet can releasably seal the opening. The bayonet is provided with a first and a third liquid inlet channel. When pushing a part of the bayonet into the opening so that the third liquid inlet channel enters the opening and enables the third liquid inlet channel to be above the opening, the channels and the accommodating cavity are communicated with each other, and when the bayonet seals the opening, the third liquid inlet channel and the accommodating cavity are not communicated with each other. The ejector pin with a first sealing ring can releasably seal the bottle body.

Abstract: Method of characterizing the chemical signature of petroleum oil contained in reservoir rock for the purpose of production allocation, estimation of vertical drainage, and monitoring of production. Reservoir rock samples from petroleum pay zones are cleaned from surface contaminations, and then loaded with water into pressure vessels and seals to airtight. The vessels are heat treated with elevated pressure to release trapped oil. Oil is extracted from the products from the vessels and analyzed for chemical compositions. The measured compositions of extracted oils are used to construct geochemical fingerprinting for the characterization of fluid-in-place in the pay zones.

Abstract: The present disclosure provides a computer-implemented method, a device, and a storage medium. The method includes inputting an image into an attention-enhanced high-resolution network (AHRNet) to extract feature maps for generating a first feature map; generating a first probability map which is concatenated with the first feature map to form a concatenated first feature map, and updating the AHRNet using the first segmentation loss; generating a second feature map, and scaling the second feature map to form a third feature map; generating a second probability map which is concatenated with the third feature map to form a concatenated third feature map, and updating the AHRNet using the second segmentation loss; generating a fourth feature map, and scaling the fourth feature map to form a fifth feature map; updating the AHRNet using the third segmentation loss and the regional level set loss; and outputting the third probability map.

Abstract: A method for pancreatic mass diagnosis and patient management includes: receiving CT images of a pancreas of a patient, the pancreas of the patient including a mass; performing a segmentation process on the CT images of the pancreas and the mass to obtain a segmentation mask of the pancreas and the mass of the patient; performing a mask-to-mesh process on the segmentation mask of the pancreas and the mass of the patient to obtain a mesh model of the pancreas and the mass of the patient; performing a classification process on the mesh model of the pancreas and the mass of the patient to identify a type and a grade of a segmented pancreatic mass; and outputting updated CT images of the pancreas of the patient, the updated CT images including the segmented pancreatic mass highlighted thereon and the type and the grade of the segmented pancreatic mass annotated thereon.

Abstract: A method, an apparatus, and a non-transitory computer readable medium for training an image processing model are provided. The method includes: acquiring a sample image comprising a target object to determine an object segmentation image of the target object in the sample image; constructing an object coordinate map corresponding to the object segmentation image according to the object segmentation image; and training an image processing model comprising a self-attention mechanism layer according to the sample image, the object segmentation image, and the object coordinate map.

Abstract: An image processing method is provided.

Abstract: A method for key point detection includes the following steps: acquiring an image to be recognized; and inputting the image to be recognized into a trained key point detection model to obtain a target heat map output by the key point detection model, the target heat map corresponding to key points in the image to be recognized. The key point detection model is configured to determine a first heat map of a first size and a second heat map of a second size corresponding to the key points in the image to be recognized and correct the second heat map according to the first heat map to obtain the target heat map; the first size being smaller than the second size.

Abstract: Image detection methods, apparatus, and storage medium are provided. The method includes: acquiring a detection image obtained through computed tomography; extracting a target body part image corresponding to a target body part from the detection image; performing first image classification and segmentation on the target body part image through a first image detection model, to determine whether a first target lesion type and a lesion region corresponding to the first target lesion type exist in the target body part image; and performing second image classification and segmentation on the target body part image through a second image detection model, to determine whether a second target lesion type and a lesion region corresponding to the second target lesion type exist in the target body part image, wherein the second target lesion type is a subcategory of the first target lesion type.

Abstract: Knowledge distillation method for fracture detection includes obtaining medical images including region-level labeled images, image-level diagnostic positive images, and image-level diagnostic negative images, in chest X-rays; performing a supervised pre-training process on the region-level labeled images and the image-level diagnostic negative images to train a neural network to generate pre-trained weights; and performing a semi-supervised training process on the image-level diagnostic positive images using the pre-trained weights. A teacher model is employed to produce pseudo ground-truths (GTs) on the image-level diagnostic positive images for supervising training of a student model, and the pseudo GTs are processed by an adaptive asymmetric label sharpening (AALS) operator to produce sharpened pseudo GTs to provide positive detection responses on the image-level diagnostic positive images.

Abstract: A preoperative survival prediction method and a computing device applying the method include constructing a data seta according to a plurality of enhanced medical images and a resection margin of each enhanced medical image and obtaining a plurality of training data sets from the constructed data set. For each training data set, multi-task prediction models are trained. A target multi-task prediction model is selected from the plurality, and a resection margin prediction value and a survival risk prediction value are obtained by predicting an enhanced medical image to be measured through the target multi-task prediction model. The multi-task prediction model more effectively captures the changes over time of the tumor in multiple stages, so as to enable a joint prediction of a resection margin prediction value and a survival risk prediction value.