Related papers: W-Net: A CNN-based Architecture for White Blood Ce…
Red blood cells are highly deformable and present in various shapes. In blood cell disorders, only a subset of all cells is morphologically altered and relevant for the diagnosis. However, manually labeling of all cells is laborious,…
The grade of clear cell renal cell carcinoma (ccRCC) is a critical prognostic factor, making ccRCC nuclei grading a crucial task in RCC pathology analysis. Computer-aided nuclei grading aims to improve pathologists' work efficiency while…
Automated red blood cell (RBC) classification on blood smear images helps hematologists to analyze RBC lab results in a reduced time and cost. However, overlapping cells can cause incorrect predicted results, and so they have to be…
Pathological diagnosis is the gold standard for cancer diagnosis, but it is labor-intensive, in which tasks such as cell detection, classification, and counting are particularly prominent. A common solution for automating these tasks is…
The detection and segmentation of white blood cells in blood smear images is a key step in medical diagnostics, supporting various downstream tasks such as automated blood cell counting, morphological analysis, cell classification, and…
Breast cancer is the most common cancer in women. Classification of cancer/non-cancer patients with clinical records requires high sensitivity and specificity for an acceptable diagnosis test. The state-of-the-art classification model -…
Accurately and quickly binuclear cell (BC) detection plays a significant role in predicting the risk of leukemia and other malignant tumors. However, manual microscopy counting is time-consuming and lacks objectivity. Moreover, with the…
We propose an image-based cellular contractile force evaluation method using a machine learning technique. We use a special substrate that exhibits wrinkles when cells grab the substrate and contract, and the wrinkles can be used to…
We present WBCBench 2026, an ISBI challenge and benchmark for automated WBC classification designed to stress-test algorithms under three key difficulties: (i) severe class imbalance across 13 morphologically fine-grained WBC classes, (ii)…
The nucleus of white blood cells (WBCs) plays a significant role in their detection and classification. Appropriate feature extraction of the nucleus is necessary to fit a suitable artificial intelligence model to classify WBCs. Therefore,…
Accurate classification of blood cells plays a key role in improving automated blood analysis for both medical and veterinary applications. This work presents a two-stage deep clustering method for classifying blood cells from…
Fully supervised change detection methods require difficult to procure pixel-level labels, while weakly supervised approaches can be trained with image-level labels. However, most of these approaches require a combination of changed and…
Counting and classifying blood cells is an important diagnostic tool in medicine. Support Vector Machines are increasingly popular and efficient and could replace artificial neural network systems. Here a method to classify blood cells is…
Wireless Capsule Endoscopy (WCE) is device to detect abnormalities in colon,esophagus,small intestinal and stomach, to distinguish bleeding in WCE images from non bleeding is a hard job by human reviewing and very time consuming.…
Automated white blood cell (WBC) classification is essential for leukemia screening but remains challenged by extreme class imbalance, long-tail distributions, and domain shift, leading deep models to overfit dominant classes and fail on…
Sickle cell anemia, which is characterized by abnormal erythrocyte morphology, can be detected using microscopic images. Computational techniques in medicine enhance the diagnosis and treatment efficiency. However, many computational…
Efficient and precise classification of histological cell nuclei is of utmost importance due to its potential applications in the field of medical image analysis. It would facilitate the medical practitioners to better understand and…
Pixel-level analysis of blood images plays a pivotal role in diagnosing blood-related diseases, especially Anaemia. These analyses mainly rely on an accurate diagnosis of morphological deformities like shape, size, and precise pixel…
Automated in-vitro cell detection and counting have been a key theme for artificial and intelligent biological analysis such as biopsy, drug analysis and decease diagnosis. Along with the rapid development of microfluidics and lab-on-chip…
Wireless capsule endoscopy (WCE) is an effective means of diagnosis of gastrointestinal disorders. Detection of informative scenes by WCE could reduce the length of transmitted videos and can help with the diagnosis. In this paper we…