ArticleBioMed research international2014
Diagnosis system for hepatocellular carcinoma based on fractal dimension of morphometric elements integrated in an artificial neural network.
Article in BioMed research international, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 27 citations in OpenAlex.
- NucVerse3D: generalizable 3D nuclear instance segmentation across heterogeneous microscopy modalities.Scientific reports · 2026Article
- Harnessing the Power of AI for Enhanced Diagnosis and Treatment of Hepatocellular Carcinoma.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2024Review
- Lung and Colon Cancer Detection Using a Deep AI Model.Cancers · 2024Article
- Fractal nature of human gastrointestinal system: Exploring a new era.World journal of gastroenterology · 2023Review
- Revisiting artificial intelligence diagnosis of hepatocellular carcinoma with DIKWH framework.Frontiers in genetics · 2023Review
- Nuclear morphometry and chromatin texture changes in hepatocellular carcinoma samples may predict outcomes of liver transplanted patients.BMC gastroenterology · 2022Article
- Resource Management through Artificial Intelligence in Screening Programs-Key for the Successful Elimination of Hepatitis C.Diagnostics (Basel, Switzerland) · 2022Article
- Interleukin-1α and -1β assessment in the gingival crevicular fluid of periodontal patients with chronic hepatitis C.Experimental and therapeutic medicine · 2020Article
- Automated Gleason grading of prostate cancer using transfer learning from general-purpose deep-learning networks.Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie · 2020Article
- Diagnosis of Liver Neoplasms by Computational and Statistical Image Analysis.Gastroenterology research · 2019Article
- Small Cell Lung Cancer Therapeutic Responses Through Fractal Measurements: From Radiology to Mitochondrial Biology.Journal of clinical medicine · 2019Article
- Computer Aided Diagnosis for Confocal Laser Endomicroscopy in Advanced Colorectal Adenocarcinoma.PloS one · 2016Article
- The Application of Classification and Regression Trees for the Triage of Women for Referral to Colposcopy and the Estimation of Risk for Cervical Intraepithelial Neoplasia: A Study Based on 1625 Cases with Incomplete Data from Molecular Tests.BioMed research international · 2015Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimsHepatocellular carcinoma (HCC) remains a leading cause of death by cancer worldwide. Computerized diagnosis systems relying on novel imaging markers gained significant importance in recent years. Our aim was to integrate a novel morphometric measurement--the fractal dimension (FD)--into an artificial neural network (ANN) designed to diagnose HCC. MATERIAL AND
methodsThe study included 21 HCC and 28 liver metastases (LM) patients scheduled for surgery. We performed hematoxylin staining for cell nuclei and CD31/34 immunostaining for vascular elements. We captured digital images and used an in-house application to segment elements of interest; FDs were calculated and fed to an ANN which classified them as malignant or benign, further identifying HCC and LM cases.
resultsUser intervention corrected segmentation errors and fractal dimensions were calculated. ANNs correctly classified 947/1050 HCC images (90.2%), 1021/1050 normal tissue images (97.23%), 1215/1400 LM (86.78%), and 1372/1400 normal tissues (98%). We obtained excellent interobserver agreement between human operators and the system.
conclusionWe successfully implemented FD as a morphometric marker in a decision system, an ensemble of ANNs designed to differentiate histological images of normal parenchyma from malignancy and classify HCCs and LMs.
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