AIMC Topic: Hematoxylin

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A deep learning framework deploying segment anything to detect pan-cancer mitotic figures from haematoxylin and eosin-stained slides.

Communications biology Dec 19, 2024
Mitotic activity is an important feature for grading several cancer types. However, counting mitotic figures (cells in division) is a time-consuming and laborious task prone to inter-observer variation. Inaccurate recognition of MFs can lead to incor...
Hematoxylin Image Processing, Computer-Assisted Staining and Labeling Mitosis Eosine Yellowish-(YS) Humans Neoplasms Deep Learning
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CIMIL-CRC: A clinically-informed multiple instance learning framework for patient-level colorectal cancer molecular subtypes classification from H&E stained images.

Computer methods and programs in biomedicine Nov 19, 2024
BACKGROUND AND OBJECTIVE: Treatment approaches for colorectal cancer (CRC) are highly dependent on the molecular subtype, as immunotherapy has shown efficacy in cases with microsatellite instability (MSI) but is ineffective for the microsatellite sta...
Humans Deep Learning Image Processing, Computer-Assisted Principal Component Analysis Microsatellite Instability Neural Networks, Computer Machine Learning Algorithms Colorectal Neoplasms Eosine Yellowish-(YS) Hematoxylin
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Cell Segmentation With Globally Optimized Boundaries (CSGO): A Deep Learning Pipeline for Whole-Cell Segmentation in Hematoxylin-and-Eosin-Stained Tissues.

Laboratory investigation; a journal of technical methods and pathology Nov 9, 2024
Accurate whole-cell segmentation is essential in various biomedical applications, particularly in studying the tumor microenvironment. Despite advancements in machine learning for nuclei segmentation in hematoxylin and eosin (H&E)-stained images, the...
Carcinoma, Hepatocellular Image Processing, Computer-Assisted Staining and Labeling Eosine Yellowish-(YS) Hematoxylin Algorithms Tumor Microenvironment Deep Learning Liver Neoplasms Humans
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An interpretable deep learning model for detecting pathogenic variants of breast cancer from hematoxylin and eosin-stained pathological images.

PeerJ Oct 28, 2024
BACKGROUND: Determining the status of breast cancer susceptibility genes () is crucial for guiding breast cancer treatment. Nevertheless, the need for genetic testing among breast cancer patients remains unmet due to high costs and limited resources...
Genetic Predisposition to Disease Mutation Eosine Yellowish-(YS) Hematoxylin Adult Humans Breast Neoplasms Algorithms Middle Aged Female Deep Learning
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Artificial intelligence can be trained to predict -11 mutational status of canine mast cell tumors from hematoxylin and eosin-stained histological slides.

Veterinary pathology Oct 18, 2024
Numerous prognostic factors are currently assessed histologically and immunohistochemically in canine mast cell tumors (MCTs) to evaluate clinical behavior. In addition, polymerase chain reaction (PCR) is often performed to detect internal tandem dup...
Artificial Intelligence Sensitivity and Specificity Animals Dog Diseases Proto-Oncogene Proteins c-kit Eosine Yellowish-(YS) Hematoxylin Deep Learning Staining and Labeling Mutation Dogs
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Weakly supervised deep learning image analysis can differentiate melanoma from naevi on haematoxylin and eosin-stained histopathology slides.

Journal of the European Academy of Dermatology and Venereology : JEADV Aug 31, 2024
BACKGROUND: The broad histomorphological spectrum of melanocytic pathologies requires large data sets to develop accurate and generalisable deep learning (DL)-based diagnostic pathology classifiers. Weakly supervised DL promotes utilisation of larger...
Nevus Aged Eosine Yellowish-(YS) Aged, 80 and over Hematoxylin Adult Male Middle Aged Deep Learning Staining and Labeling Diagnosis, Differential Humans Female Melanoma Skin Neoplasms
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An Immunofluorescence-Guided Segmentation Model in Hematoxylin and Eosin Images Is Enabled by Tissue Artifact Correction Using a Cycle-Consistent Generative Adversarial Network.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Aug 13, 2024
Despite recent advances, the adoption of computer vision methods into clinical and commercial applications has been hampered by the limited availability of accurate ground truth tissue annotations required to train robust supervised models. Generatin...
Image Interpretation, Computer-Assisted Artifacts Fluorescent Antibody Technique Eosine Yellowish-(YS) Hematoxylin Humans Deep Learning Image Processing, Computer-Assisted Staining and Labeling
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Deep learning for rapid virtual H&E staining of label-free glioma tissue from hyperspectral images.

Computers in biology and medicine Aug 1, 2024
Hematoxylin and eosin (H&E) staining is a crucial technique for diagnosing glioma, allowing direct observation of tissue structures. However, the H&E staining workflow necessitates intricate processing, specialized laboratory infrastructures, and spe...
Hyperspectral Imaging Eosine Yellowish-(YS) Hematoxylin Image Processing, Computer-Assisted Staining and Labeling Glioma Humans Brain Neoplasms Deep Learning
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Novel Artificial Intelligence Combining Convolutional Neural Network and Support Vector Machine to Predict Colorectal Cancer Prognosis and Mutational Signatures From Hematoxylin and Eosin Images.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Jul 15, 2024
Reducing recurrence following radical resection of colon cancer without overtreatment or undertreatment remains a challenge. Postoperative adjuvant chemotherapy (Adj) is currently administered based solely on pathologic TNM stage. However, prognosis ...
Male Middle Aged Support Vector Machine Neoplasm Staging Female Aged Mutation Colorectal Neoplasms Humans Neoplasm Recurrence, Local Neural Networks, Computer Eosine Yellowish-(YS) Artificial Intelligence Hematoxylin Prognosis
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Prediction of molecular subclasses of uveal melanoma by deep learning using routine haematoxylin-eosin-stained tissue slides.

Histopathology Jul 1, 2024
AIMS: Uveal melanoma has a high propensity to metastasize. Prognosis is associated with specific driver mutations and copy number variations, and these can only be obtained after genetic testing. In this study we evaluated the efficacy of patient out...
Staining and Labeling Mutation Phosphoproteins Tumor Suppressor Proteins Eosine Yellowish-(YS) Hematoxylin RNA Splicing Factors Humans Uveal Neoplasms Prognosis Adult Retrospective Studies Male Female Melanoma Ubiquitin Thiolesterase Middle Aged Aged Deep Learning Uveal Melanoma Aged, 80 and over Eukaryotic Initiation Factor-1
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