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Tomography, Volume 11, Issue 1

January 2025 - 10 articles

Cover Story: Accurate kidney tumor segmentation in CT scans is critical for diagnosis and treatment, yet manual methods lack efficiency. This study introduces an AI model combining vision transformers (ViTs) and convolutional neural networks (CNNs) for automated tumor segmentation. Trained on public data and validated on an independent institutional dataset, it demonstrates real-world clinical potential and utility in early detection. Tumors, categorized by TNM staging as small (≤4 cm), medium (>4–≤7 cm), and large (>7 cm), achieved Dice scores of 0.84, 0.89, and 0.92 on institutional data. These results highlight the model’s precision and robustness, paving the way for improved radiological accuracy and earlier intervention in clinical practice. View this paper

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Articles (10)

  • Article
  • Open Access
1,919 Views
16 Pages

Objectives: To evaluate the effectiveness of breast MRI, including diffusion-weighted imaging (DWI), in detecting residual lesions in patients with malignancy after excisional biopsy. Methods: From January 2018 to December 2023, 3T breast MRI was per...

  • Article
  • Open Access
2 Citations
1,601 Views
11 Pages

Background/Objectives: The aim was to investigate the association between variations in the dorsal pancreatic artery (DPA) and intrapancreatic arcade anatomy with Whipple procedure outcomes and postoperative complications. Methods: This retrospective...

  • Article
  • Open Access
1 Citations
2,131 Views
15 Pages

Comparative Sensitivity of MRI Indices for Myelin Assessment in Spinal Cord Regions

  • Philip Kyeremeh Jnr Oppong,
  • Hiroyuki Hamaguchi,
  • Maho Kitagawa,
  • Nina Patzke,
  • Kevin C. Wakeman and
  • Khin Khin Tha

Background/Objectives: Although multiple magnetic resonance imaging (MRI) indices are known to be sensitive to the noninvasive assessment of myelin integrity, their relative sensitivities have not been directly compared. This study aimed to identify...

  • Article
  • Open Access
1,972 Views
15 Pages

Fast Hadamard-Encoded 7T Spectroscopic Imaging of Human Brain

  • Chan Hong Moon,
  • Frank S. Lieberman,
  • Hoby P. Hetherington and
  • Jullie W. Pan

Background/Objectives: The increased SNR available at 7T combined with fast readout trajectories enables accelerated spectroscopic imaging acquisitions for clinical applications. In this report, we evaluate the performance of a Hadamard slice encodin...

  • Commentary
  • Open Access
1 Citations
2,021 Views
8 Pages

This commentary examines Topological Data Analysis (TDA) in radiology imaging, highlighting its revolutionary potential in medical image interpretation. TDA, which is grounded in mathematical topology, provides novel insights into complex, high-dimen...

  • Technical Note
  • Open Access
2 Citations
1,680 Views
15 Pages

The Role of 3D Virtual Anatomy and Scanning Environmental Electron Microscopy in Understanding Morphology and Pathology of Ancient Bodies

  • Sara Salucci,
  • Mirko Traversari,
  • Laura Valentini,
  • Ilaria Versari,
  • Luca Ventura,
  • Emanuela Giampalma,
  • Elena Righi,
  • Enrico Petrella,
  • Pietro Gobbi and
  • Gianandrea Pasquinelli
  • + 1 author

Background/Objectives: Mummy studies allow to reconstruct the characteristic of a population in a specific spatiotemporal context, in terms of living conditions, pathologies and death. Radiology represents an efficient diagnostic technique able to es...

  • Article
  • Open Access
2,194 Views
15 Pages

Metabolic Differences in Neuroimaging with [18F]FDG in Rats Under Isoflurane and Hypnorm–Dormicum

  • Aage Kristian Olsen Alstrup,
  • Mette Simonsen,
  • Kim Vang Hansen and
  • Caroline C. Real

Background: Anesthesia can significantly impact positron emission tomography (PET) neuroimaging in preclinical studies. Therefore, understanding these effects is crucial for accurate interpretation of the results. In this experiment, we investigate t...

  • Article
  • Open Access
6 Citations
3,307 Views
15 Pages

Dual-Stage AI Model for Enhanced CT Imaging: Precision Segmentation of Kidney and Tumors

  • Nalan Karunanayake,
  • Lin Lu,
  • Hao Yang,
  • Pengfei Geng,
  • Oguz Akin,
  • Helena Furberg,
  • Lawrence H. Schwartz and
  • Binsheng Zhao

Objectives: Accurate kidney and tumor segmentation of computed tomography (CT) scans is vital for diagnosis and treatment, but manual methods are time-consuming and inconsistent, highlighting the value of AI automation. This study develops a fully au...

  • Article
  • Open Access
2 Citations
1,825 Views
15 Pages

Effective Dose Estimation in Computed Tomography by Machine Learning

  • Matteo Ferrante,
  • Paolo De Marco,
  • Osvaldo Rampado,
  • Laura Gianusso and
  • Daniela Origgi

Background: Computed tomography scans are widely used in everyday medical practice due to speed, image reliability, and detectability of a wide range of pathologies. Each scan exposes the patient to a radiation dose, and performing a fast estimation...

  • Article
  • Open Access
1,658 Views
20 Pages

Due to the increasing number of people working at computers in professional settings, the incidence of lumbar disc herniation is increasing. Background/Objectives: The early diagnosis and treatment of lumbar disc herniation is much more likely to yie...

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Tomography - ISSN 2379-139X