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Journal of Liver Transplantation is a peer-reviewed journal published by Elsevier, covering Organ Transplantation Techniques and Outcomes, Liver Disease and Transplantation, Liver Disease Diagnosis and Treatment.
| Publisher | Elsevier |
|---|---|
| Reference style | Numbered (Elsevier) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, C. Lee, A representative article title, Journal of Liver Transplantation 12 (2023) 45–58.
Formats any DOI in Journal of Liver Transplantation style. No sign-up. |
| Publishes research in | Organ Transplantation Techniques and Outcomes Liver Disease and Transplantation Liver Disease Diagnosis and Treatment Renal Transplantation Outcomes and Treatments Organ Donation and Transplantation |
| ISSN | 2666-9676 |
| Citation impact (2-yr) | 0.85 |
| h-index | 9 |
| i10-index | 7 |
| Total citations | 424 |
| Article processing charge | $1,941 |
| Open access | Yes |
| Top institutions publishing here | Max Super Speciality Hospital |
| Journal website | www.journals.elsevier.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Segmenting the liver and tumors from computed tomography (CT) scans is crucial for medical studies utilizing machine and deep learning techniques. Semantic segmentation, a critical step in this process, is accomplished effectively using fully convolutional neural networks (CNNs). Most Popular networks like UNet and ResUNet leverage diverse resolution features through meticulous planning of convolutional layers…
Diagnosing liver diseases using computed tomography (CT) images can be challenging even for experienced radiologists due to the complexities involved in evaluating the liver. Accurately determining the type, size and severity of tumors is often difficult. In recent years there has been a growing need for computer-assisted imaging techniques to aid in liver disease diagnosis…
The precision of liver tumor segmentation heavily depends on the doctor's expertise, hence it is required to produce an algorithm for automatic liver tumor segmentation to reduce the manual intervention in assessing liver disease identification. We propose a CNN-based UNet architecture designed to segment liver tumors from CT images of size 128×128. In this model,…
Liver transplantation is the only radical treatment option available for patients with end-stage chronic liver disease. However, severe post-transplant complications remain relevant, including acute graft rejection and infection. Thus, the impact of gut microbiota on the frequency of these complications is highly promising. This prospective, cohort, closed-label study included 24 adults who underwent liver transplantation.…
Detecting macrovesicular steatosis (MS) in live and deceased donor livers is crucial. Studies have unequivocally shown that the severity of MS correlates with adverse post-LT outcomes. The degree of MS is intimately related to the viability of the liver graft, which in turn is crucial to the success of the operation. A conventional liver biopsy…
