The Cirrhotic Liver Patients dataset was collected from (\textbf{***blinded information***}), it provides a valuable resource for improving clinical diagnosis through advancing research in automated liver cirrhosis analysis. Focusing exclusively on patients with liver cirrhosis, our proposed dataset reflects real-world complexities by including scans with distinct morphological alterations. These alterations include contour nodularity, hepatic segment atrophy or hypertrophy, all contributing to the dataset's variability and complexity. This complexity is essential for training robust and generalizable DL models that can perform well on unseen data. To further enhance the dataset's representativeness, we incorporated liver MRI scans with less common features like parenchymal texture variations, focal liver lesions, and intrahepatic portal vein thromboses. This inclusion broadened the range of disease presentations within the dataset, making it more reflective of real-world clinical scenarios. Figure~\ref{fig:fibrosis_stages} shows the diverse visual presentations of cirrhosis across different stages, ranging from mild fibrosis to advanced disease. The first images in each row (top left and bottom left) depict minimal visible fibrotic tissue, despite representing cirrhotic livers. This highlights the limitations of relying solely on visual assessment, particularly for earlier stages of cirrhosis. The top row shows T1-weighted (T1W) and the second row shows the same stages in T2-weighted (T2W). Earlier-stage cirrhosis is often missed in diagnosis, leading many patients to present with decompensated cirrhosis or HCC at a later stage of the disease~\cite{naturereview}. This is a major concern because morbidity and mortality rates in CLD patients increase with both advanced fibrosis stage and progression from compensated to decompensated cirrhosis~\cite{sharma}. **Patient Data and MRI acquisition:** We made the specific protocol for MRI data acquisition. (1) The study included only patients with liver cirrhosis; patients with normal abdomen and healthy livers were excluded. (2) The imaging quality had to be good enough (i.e., QA should have been passed) so that participating radiologists can annotate and review the volumetric scans. (3) We aimed to collect volumetric scans from three different scanners to maintain heterogeneity. MRI scans (T1W and T2W) were obtained from the Achieva Philips Medical system scanners (1.5T and 3T) and Siemens Symphony 1.5T with full anonymization protocol. The majority (over 95\%) of T1-weighted scans were post-contrast and from the portal venous phase for improved organ contrast. There were also mild to moderate artifacts in the MRI scans (like motion or susceptibility). (4) We aimed to capture comprehensive liver cirrhosis examples with different etiologies and stages emphasizing the variability and diverse complications. It is to be noted that we excluded the volumetric scans with poor image quality and significant motion artifacts.