Waveform & Radiomics Analysis

Transforming high-dimensional physiological signals and medical imaging data into quantitative, clinically meaningful insights.

Aganitha’s Quantitative Imaging Across Human and Preclinical Models

Physiological waveform and imaging data span both clinical (human) and preclinical (animal) research, but differ significantly in structure, scale, and interpretation. Variations in heart rate, neural dynamics, and signal morphology require species-specific approaches to preprocessing, feature extraction, and event detection. Similarly, preclinical imaging often achieves higher resolution and sensitivity, while clinical workflows prioritize standardization, safety, and population variability.

Aganitha’s pipelines are designed to account for these differences while maintaining analytical consistency. We enable robust human and animal waveform analysis, supporting both within-species interpretation and cross-species comparability essential for translational research.

By integrating temporal waveform analytics with radiomics-based imaging features, we deliver multi-scale phenotyping — linking physiological signals with structural insights to support cohort analysis, longitudinal modeling, and preclinical-to-clinical translation.

Waveform analysis

Radiomics

1. Waveform analysis

Physiological signals – from heart rhythms to brain waves to muscle activity – carry dense temporal information. Aganitha’s waveform pipelines preprocess, segment, and classify these 1D time-series signals to extract clinically meaningful features in real time or from archived recordings.

ECG analysis

R-peak detection, QRS complex segmentation, HRV computation, arrhythmia classification (AFib, bradycardia, tachycardia, premature contractions), and myocardial infarction detection by territory.

EEG analysis

Brain wave decomposition (delta through gamma), seizure detection from high-amplitude discharge patterns, sleep stage classification (N1–N3, REM), and cognitive state monitoring

EMG analysis

Surface and intramuscular EMG processing – burst detection, gesture classification (open/fist/grip/point), motor unit action potential analysis, muscle fatigue quantification, and onset detection.

What Aganitha delivers

We focus on transforming time-series physiological signals such as EEG, ECG, and EMG into structured, interpretable insights through robust, multi-scale analytical pipelines.
We perform signal preprocessing, feature extraction, and statistical modeling to capture both rapid events and sustained activity patterns, enabling automated detection and characterization of clinically relevant events such as seizures or arrhythmias, including their onset, duration, and intensity.
Our approach incorporates temporal modeling to uncover cyclic and longitudinal patterns, alongside phenotype segmentation that converts continuous signals into biologically meaningful states.
Extending beyond individual samples, we enable cohort-level comparison, stratification, and longitudinal disease modeling, delivering quantitative phenotypes and decision-ready insights that support preclinical and clinical research.

3. Radiomics

Radiomics converts 3D volumetric scans into hundreds of quantitative biomarkers — shape, texture, intensity, and wavelet features — that are invisible to the naked eye. Aganitha applies this to MRI, PET/CT, and multimodal fusion workflows for tumor phenotyping, treatment response prediction, and survival modeling.

PET/CT radiomics

High-content fluorescent imaging analysis – phenotypic fingerprinting across images, mechanism-of-action prediction, compound classification, and disease signature profiling from multi-channel morphological profiles.

X-ray radiomics

Live-cell imaging analysis for organoid growth kinetics, toxicity screening, motility and tracking, and spheroid morphometry – with optional virtual H&E transformation from label-free images.

MRI radiomics

Multi-gigapixel whole slide image analysis – nuclei segmentation, cell-type quantification, tumor grading, tissue classification, and morphological feature extraction using deep learning instance segmentation.

Ultrasound analysis

2D and 3D ultrasound processing – organ morphometry, disease classification, tissue characterization (benign vs malignant), fetal measurements, and cardiac segmentation from B-mode and Doppler images.

What Aganitha Delivers

Challenges in manufacturing rare disease treatments have spurred innovation, resulting in cost-effective processes that benefit rare and common disease treatments

Why Aganitha

The Aganitha Advantage

Biology-First AI

Our models are designed with domain expertise, trained and validated by scientists who understand the biological context, not just the pixel statistics.

2D to 3D Native

Native support for 2D and 3D imaging modalities, including organoid and tissue section analysis.

Label-Free Intelligence

Brightfield and virtual staining pipelines reduce dependency on expensive fluorescent protocols while preserving analytical richness across phenotypic endpoints.

Multi-Modal Ready

Engineered for integration with genomics, transcriptomics, and proteomics, delivering a unified view of biological state that imaging alone cannot provide.

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Our Solutions

Customizable platforms and solutions across the drug discovery value chain from target discovery to therapeutic development

Our Services

Offering services in computational sciences and technology to complement biopharma R&D

Case Studies

Helping clients accelerate drug discovery and development by building computational biology, computational chemistry, technology, and cloud solutions