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Found 8 papers, 2 papers with code
'Aariz: A Benchmark Dataset for Automatic Cephalometric Landmark Detection and CVM Stage Classification
The accurate identification and precise localization of cephalometric landmarks enable the classification and quantification of anatomical abnormalities.
CEPHA29: Automatic Cephalometric Landmark Detection Challenge 2023
Quantitative cephalometric analysis is the most widely used clinical and research tool in modern orthodontics.
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images
Medical image segmentation assists in computer-aided diagnosis, surgeries, and treatment.
Ranked #3 on
Medical Image Segmentation
on GlaS
(IoU metric)
Nuclei & Glands Instance Segmentation in Histology Images: A Narrative Review
Instance segmentation of nuclei and glands in the histology images is an important step in computational pathology workflow for cancer diagnosis, treatment planning and survival analysis.
Vision Transformers in Medical Computer Vision -- A Contemplative Retrospection
Among these algorithms, Vision Transformers are evolved as one of the most contemporary and dominant architectures that are being used in the field of computer vision.
Person Re-identification: A Retrospective on Domain Specific Open Challenges and Future Trends
Person re-identification (Re-ID) is one of the primary components of an automated visual surveillance system.
Orientation Aware Weapons Detection In Visual Data : A Benchmark Dataset
For training our model for weapon detection a new dataset comprising of total 6400 weapons images is gathered from the web and then manually annotated with position oriented bounding boxes.
Context-Aware Convolutional Neural Network for Grading of Colorectal Cancer Histology Images
Digital histology images are amenable to the application of convolutional neural network (CNN) for analysis due to the sheer size of pixel data present in them.
