Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
April 15, 2026Iconic Research and Engineering Journals

Liver Tumor Detection Using Deep Learning

View Full Paper
Ask AI
Bookmark
Share

Authors

SVSoniya Komal VBSBajarang SNDN Darshan

Discussion

Loading...

Member takes

Overview

This research demonstrates a deep learning approach to enhance liver tumor detection in medical imaging, suggesting improved diagnostic accuracy.

Key Points

  • The aim is to develop a deep learning model for early liver tumor detection from CT images.
  • Utilized a 3D U-Net architecture for tumor segmentation from CT scans.
  • Incorporated the Bat Algorithm for hyperparameter optimization.
  • Preprocessed CT images through normalization, resizing, and augmentation.
  • Achieved high accuracy in liver tumor detection.
  • Maintained a good balance between true positives and false detections.
  • Demonstrated robust performance in identifying tumors across various cases.

Cite This Study

V et al. (2026) studied this question.

synapsesocial.com/papers/69df2c01e4eeef8a2a6b0efbhttps://doi.org/10.64388/irev9i10-1716185
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Deep Learning Driven Liver Tumor Detection and Classification2024
  2. 2Liver cancer detection using Artificial Intelligence2024 · 1 citations
  3. 3A Comprehensive Liver Tumor Detection and Stages Classification Using Deep Learning and Image Processing Techniques2024 · 5 citations
  4. 4Automatic segmentation of liver tumors from computed tomographic images using hybrid deep learning model2026
  5. 5A comprehensive review on deep learning for liver cancer detection: research challenges and future directions2026